629 Xgboost Jobs - Page 5

You will be responsible for developing machine learning models by designing, building, and evaluating both supervised and unsupervised models like regression, classification, clustering, and recommendation systems. This includes performing feature engineering, model tuning, and validation through cross-validation and various performance metrics. Your duties will also involve preparing and analyzing data by cleaning, preprocessing, and transforming large datasets sourced from different channels. You will conduct exploratory data analysis (EDA) to reveal patterns and gain insights from the data. In addition, you will deploy machine learning models into production using tools like Flask, FastAPI, or cloud-native services. Monitoring model performance and updating or retraining models as necessary will also fall under your purview. Collaboration and communication are key aspects of this role as you will collaborate closely with data engineers, product managers, and business stakeholders to comprehend requirements and provide impactful solutions. Furthermore, presenting findings and model outcomes in a clear and actionable manner will be essential. You will utilize Python and libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch. Additionally, leveraging version control tools like Git, Jupyter notebooks, and ML lifecycle tools such as MLflow and DVC will be part of your daily tasks. The ideal candidate should possess a Bachelor's or Master's degree in computer science, Data Science, Statistics, or a related field. A minimum of 2-3 years of experience in building and deploying machine learning models is preferred. Strong programming skills in Python and familiarity with SQL are required. A solid grasp of ML concepts, model evaluation, statistical techniques, exposure to cloud platforms (AWS, GCP, or Azure), and MLOps practices would be advantageous. Excellent problem-solving and communication skills are also essential for this role.,

Job Title: Senior Clinical Data Scientist / Clinical Data Analyst Experience: 7+ Years Location: Bangalore / Chennai / Hyderabad / Noida / Gurgaon (India) Industry: Pharmaceutical / Healthcare / Life Sciences Employment Type: Full-time Job Summary: We are seeking a highly experienced and analytical Senior Clinical Data Scientist / Analyst with 7+ years of experience in clinical data analysis, pharmaceutical research, and data science methodologies . The ideal candidate will have hands-on experience working with EMR/EHR data , advanced SQL , and machine learning models to derive actionable insights that support clinical research and drug development. Key Responsibilities: Analyze and interpret complex clinical and EMR data to support real-world evidence (RWE), HEOR, and clinical trial analysis. Design and develop statistical and machine learning models to predict patient outcomes, drug efficacy, and safety. Perform deep-dive analytics using Advanced SQL (CTE, RANK, PARTITION) for cohort identification and data transformation. Collaborate with cross-functional teams including biostatisticians, clinical operations, and regulatory affairs. Ensure data quality and integrity from diverse sources like EMR, claims, lab systems, and clinical trial management systems (CTMS). Automate data pipelines and implement best practices in reproducible analytics. Create dashboards, data visualizations, and reports for stakeholders and medical affairs teams. Stay up to date with current industry trends in real-world data (RWD), clinical informatics, and regulatory requirements. Required Skills: 7+ years of experience in clinical data analytics or data science within the Pharma/Healthcare domain . Strong expertise in Advanced SQL : CTEs, Window Functions (RANK, DENSE_RANK, PARTITION BY), joins, subqueries. Experience working with EMR/EHR systems such as Epic, Cerner, Meditech, etc. Proficiency in Python, R , or SAS for statistical and machine learning modeling. Strong knowledge of clinical trial design , ICD/CPT coding , MedDRA , and pharmacovigilance datasets. Hands-on with machine learning frameworks (Scikit-learn, XGBoost, etc.) for prediction and classification tasks. Familiarity with regulatory guidelines such as HIPAA , GCP , and 21 CFR Part 11 . Experience with data visualization tools such as Tableau, Power BI, or Python-based dashboards . Preferred Qualifications: Master’s or Ph.D. in Data Science, Biostatistics, Bioinformatics, Public Health, or a related field . Prior experience in RWE/RWD analytics , HEOR studies , or pharma R&D analytics . Knowledge of CDISC SDTM/ADaM standards . Experience working with cloud platforms (AWS, Azure, GCP) and data lake architecture is a plus. Job Type: Contractual / Temporary Contract length: 12 months Schedule: US shift Application Question(s): What would your NP? Which location would you pick Bangalore / Chennai / Hyderabad / Noida / Gurgaon (India) Experience: Data science: 5 years (Preferred) Machine learning: 5 years (Preferred) EMR systems: 5 years (Preferred) Work Location: In person

The ML Solutions team within Markets OPS Technology is dedicated to developing solutions using Artificial Intelligence, Machine Learning, and Generative AI. This team is a leader in creating new ideas, innovative technology solutions, and ground-breaking solutions for Markets Operations and Other Line of Businesses. We work closely with our clients and business partners to progress solutions from ideation to production by leveraging the entrepreneurial spirit and technological excellence. The ML Solutions team is seeking a Data Scientist/Machine Learning Engineer to drive the design, development, and deployment of innovative AI/ML and GenAI-based solutions. In this hands-on role, you will leverage your expertise to create a variety of AI models, guiding a team from initial concept to successful production. A key aspect involves mentoring team members and fostering their growth. You will collaborate closely with business partners and stakeholders, championing the adoption of these advanced technologies to enhance client experiences, deliver tangible value to our customers, and ensure adherence to regulatory requirements through cutting-edge technical solutions. This position offers a unique opportunity to shape the future of our AI initiatives and make a significant impact on the organization. Key Responsibilities: - Hands-On Execution and Delivery: Actively contribute to the development and delivery of AI solutions, driving innovation and excellence within the team. Take a hands-on approach to ensure AI models are successfully deployed into production environments, meeting high-quality standards and performance benchmarks. - Mentoring Young Talents: Mentoring team, guiding data analysts/ML engineers from concept to production. This involves fostering technical growth, providing project oversight, and ensuring adherence to best practices, ultimately building a high-performing and innovative team. - Quality Control: Ensure the quality and performance of generative AI models, conducting rigorous testing and evaluation. - Research and Development: Participate in research activities to explore and advance state-of-the-art generative AI techniques. Stay actively engaged in monitoring ongoing research efforts, keeping abreast of emerging trends, and ensuring that the Generative AI team remains at the forefront of the field. - Cross-Functional Collaboration: Collaborate effectively with various teams, including product managers, engineers, and data scientists, to integrate AI technologies into products and services. Skills & Qualifications: - 8 to 13 years of Strong hands-on experience in Machine Learning, delivering complex solutions to production. - Experience with Generative AI technologies essential. - Understanding of concepts like supervised, unsupervised, clustering, embedding. - Knowledge of NLP, Name Entity Recognition, Computer Vision, Transformers, Large Language Models. - In-depth knowledge of deep learning and Generative AI frameworks such as, Langchain, Lang Graph, Crew AI or similar. - Experience with and other open-source frameworks/ libraries/ APIs like Hugging Face Transformers, Spacy, Pandas, scikit-learn, NumPy, OpenCV. - Experience in using Machine Learning/Deep Learning: XGBoost, LightGBM, TensorFlow, PyTorch, Keras. - Proficiency in Python Software Development, following Object-Oriented design patterns and best practices. - Strong background in mathematics: linear algebra, probability, statistics, and optimization. - Experience with evaluation, scoring with a framework like ML Flow - Experience of Docker container and edited a Docker file, experience with K8s is a plus. - Experience with Postgres and Vector DBs a plus. - Excellent problem-solving skills and the ability to think creatively. - Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams - Publications and contributions to the AI research community are a plus. - Masters degree/Ph. D. or equivalent experience in Computer Science, Data Science, Statistics, or a related field. - 8-12 years of experience This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.,

Job Description : Principal AI Architect Employment Type : Full-Time. Relevant Experience : 10+ years Key Responsibilities AI-First Leadership : Define and drive DB Techs AI vision, re-architect systems into AI-native services, integrate tools like Cursor/Relevance AI, and mentor teams in prompt engineering, Vibe Coding, and autonomous testing. Architect Scalable AI Systems : Design enterprise-scale AI/ML platforms that support real-time analytics, model deployment, and continuous learning in financial products and services. Lead Solution Design : Collaborate with data scientists, engineers, and business stakeholders to build and integrate AI models into core platforms (e.g., risk engines, transaction monitoring, robo-advisors). Ensure Governance & Compliance : Implement AI systems that meet financial regulations (e.g., GDPR, PCI-DSS, FFIEC, Basel III) and uphold fairness, explainability, and accountability. Drive MLOps Strategy : Establish and maintain robust pipelines for data ingestion, feature engineering, model training, testing, deployment, and monitoring. Team Leadership : Provide technical leadership to data science and engineering teams. Promote best practices in AI ethics, version control, and reproducibility. Identify areas where AI can deliver business value and lead the development of proofs-of-concept (PoCs). Evaluate the feasibility, cost, and impact of new AI initiatives. Define best practices\standards for model lifecycle management (training, validation, deployment, monitoring) - Evaluate Emerging Technologies : Stay ahead of developments in generative AI, LLMs, and FinTech- specific AI tools, and drive their strategic adoption. Technical Skills And Tools ML & AI Frameworks : Scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch Hugging Face Transformers, OpenAI APIs (for generative and NLP use cases) MLOps & Deployment MLflow, Kubeflow, Seldon Core, KServe, Weights & Biases FastAPI, gRPC, Docker, Kubernetes, Airflow FinTech-Specific Applications Credit scoring models, Fraud detection algorithms Time series forecasting, NLP for financial documents/chatbots Algorithmic trading models, AML (Anti-Money Laundering) systems Cloud & Data Platforms AWS SageMaker, Azure ML, Google Vertex AI Databricks, Snowflake, Kafka, BigQuery, Delta Lake Monitoring & Explainability SHAP, LIME, Alibi, Evidently AI, Arize AI IBM AIX 360, Fiddler AI Required Qualifications Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a related field; PhD is a plus. 10+ years of experience in AI/ML, including 35 years in architectural roles within FinTech or other highly regulated industries. Proven track record of building and deploying AI solutions in areas such as fraud detection, credit risk modeling, or portfolio optimization. Strong Hands-on Expertise In Machine Learning : scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch Data Engineering : Spark, Kafka, Airflow, SQL/NoSQL (MongoDB, Neo4j) Cloud & MLOps : AWS, GCP, or Azure; Docker, Kubernetes, MLflow, SageMaker, Vertex AI Programming : Python (primary); Java or Scala (optional) Solid software engineering background with experience integrating ML models into scalable production systems. Excellent communication skills with the ability to influence both technical and non-technical stakeholders. (ref:hirist.tech)

You will be responsible for building and interpreting machine learning models on real business data from the SigView platform, such as Logistic Regression, Boosted trees (Gradient boosting), Random Forests, and Decision Trees. Your tasks will include identifying data sources, integrating multiple sources or types of data, and applying data analytics expertise within a data source to develop methods to compensate for limitations and extend the applicability of the data. Moreover, you will be expected to extract data from relevant data sources, including internal systems and third-party data sources, through manual and automated web scrapping. Your role will involve validating third-party metrics by cross-referencing various syndicated data sources and determining the numerical variables to be used in the same form as they are from the raw datasets, categorized into buckets, and used to create new calculated numerical variables. You will perform exploratory data analysis using PySpark to finalize the list of compulsory variables necessary to solve the business problem and transform formulated problems into implementation plans for experiments by applying appropriate data science methods, algorithms, and tools. Additionally, you will work with offshore teams post data preparation to identify the best statistical model/analytical solution that can be applied to the available data to solve the business problem and derive actionable insights. Your responsibilities will also include collating the results of the models, preparing detailed technical reports showcasing how the models can be used and modified for different scenarios in the future to develop predictive insights. You will develop multiple reports to facilitate the generation of various business scenarios and provide features for users to generate scenarios. Furthermore, you will be interpreting the results of tests and analyses to develop insights into formulated problems within the business/customer context and provide guidance on risks and limitations. Acquiring and using broad knowledge of innovative data analytics methods, algorithms, and tools, including Spark, Elasticsearch, Python, Databricks, Azure, Power BI, Azure Cloud services, LLMs-Gen AI, and Microsoft Suite will be crucial for success in this role. This position may involve telecommuting and requires 10% travel nationally to meet with clients. The minimum requirements for this role include a Bachelor's Degree in Electronics Engineering, Computer Engineering, Data Analytics, Computer Science, or a related field plus five (5) years of progressive experience in the job offered or related occupation. Special skill requirements for this role include applying statistical methods to validate results and support strategic decisions, building and interpreting advanced machine learning models, using various tools such as Python, Scikit-Learn, XGBoost, Databricks, Excel, and Azure Machine Learning for data preparation and model validation, integrating diverse data sources using data analytics techniques, and performing data analysis and predictive model development using AI/ML algorithms. Your mathematical knowledge in Statistics, Probability, Differentiation and Integration, Linear Algebra, and Geometry will be beneficial. Familiarity with Data Science libraries such as NumPy, SciPy, and Pandas, Azure Data Factory for data pipeline design, NLTK, Spacy, Hugging Face Transformers, Azure Text Analytics, OpenAI, Word2Vec, and BERT will also be advantageous. The base salary for this position ranges from $171,000 to $190,000 per annum for 40 hours per week, Monday to Friday. If you have any applications, comments, or questions regarding the job opportunity described, please contact Piyush Khemka, VP, Business Operations, at 111 Town Square Pl., Suite 1203, Jersey City, NJ 07310.,

As a Senior ML/AI Engineer at our Technology Innovation Lab, you will be a key member of a cross-disciplinary team dedicated to advancing AI and intelligent automation at HERE. Your primary responsibility will be to develop cutting-edge machine learning systems that leverage Agentic AI, Generative AI, and foundational ML techniques to drive the next generation of applications. Collaborating closely with technical leads, researchers, and engineers, you will prototype solutions to address real-world spatial, operational, and knowledge-driven challenges. Your role will involve architecting and implementing AI-first systems using technologies such as Large Language Models (LLMs), Autonomous Multi-Agent Architectures, and Classical ML models like regression, clustering, XGBoost, SVM, and tree-based learners. Leading the development of Agentic AI solutions will be a core aspect of your role, encompassing tasks such as orchestration, memory/context management, tool invocation, and human-agent collaboration. You will also be responsible for designing and delivering end-to-end Generative AI applications for various purposes including text generation, summarization, code synthesis, image generation, and multi-modal interfaces. Your expertise in deep learning techniques, including CNNs, RNNs (LSTM, GRU), GANs, Diffusion Models, Transformers, and Graph Neural Networks, will be crucial for tackling real-world tasks in vision, language, and planning. You will collaborate across teams to translate domain-specific problems into scalable, explainable, and production-ready AI solutions while incorporating responsible AI principles. Staying at the forefront of AI research will be essential, as you evaluate and implement emerging LLM models, agentic frameworks, and open-source innovations to ensure technical currency in this rapidly evolving field. You will also design and lead experiments across advanced AI/ML areas, encompassing computer vision, NLP, LLMs, and emerging domains like quantum computing, distributed computing, 3D modeling, AR/VR, and LiDAR/drone data processing. Writing efficient, production-quality code using Python and leveraging frameworks like PyTorch, TensorFlow, and Spark for large-scale ML training and inference will be part of your daily tasks. Defining and tracking KPIs at both individual and business unit levels, in collaboration with your manager, will ensure that your work drives impactful innovation. Supporting and mentoring engineers and data scientists in best practices related to prompt design, agent workflows, evaluation frameworks, and research translation will also be part of your responsibilities. Additionally, contributing to HERE's innovation footprint through patents, internal IP development, and peer-reviewed publications will be encouraged. To qualify for this role, you should hold a Master's degree or Ph.D. in Computer Science, AI/ML, Mathematics, or a related field. Candidates with a Master's degree should have 5-7 years of experience, while Ph.D. holders may have 3-5 years of relevant experience. A strong understanding of ML fundamentals, hands-on experience with deep learning architectures, proficiency in Python, and familiarity with ML frameworks are essential qualifications. Curiosity and exposure to adjacent technologies like TinyML, Quantum Computing, or 3D modeling/AR will be considered advantageous. At HERE Technologies, we are a location data and technology platform company dedicated to empowering our customers and making a positive impact on people's lives. If you are passionate about driving innovation and creating positive change in an open world, we invite you to join us on this exciting journey.,

Job Title: Data Scientist Location: [Insert Location] Experience: 5–10 years (flexible based on expertise) Employment Type: Full-Time Compensation: [Insert Budget / Competitive as per industry standards] About the Role: We are looking for a highly skilled and innovative Data Scientist with deep expertise in Machine Learning, AI, and Cloud Technologies to join our dynamic analytics team. The ideal candidate will have hands-on experience in NLP, LLMs, Computer Vision , and advanced statistical techniques, along with the ability to lead cross-functional teams and drive data-driven strategies in a fast-paced environment. Key Responsibilities: Develop and deploy end-to-end machine learning pipelines including data preprocessing, modeling, evaluation, and production deployment. Work on cutting-edge AI/ML applications such as LLM-finetuning, NLP, Computer Vision, Hybrid Recommendation Systems , and RAG/CAG techniques . Leverage platforms like AWS (SageMaker, EC2) and Databricks for scalable model development and deployment. Handle data at scale using Spark, Python, SQL , and integrate with NoSQL and Vector Databases (Neo4j, Cassandra) . Design interactive dashboards and visualizations using Tableau for actionable insights. Collaborate with cross-functional stakeholders to translate business problems into analytical solutions. Guide data curation efforts and ensure high-quality training datasets for supervised and unsupervised learning. Lead initiatives around AutoML, XGBoost, Topic Modeling (LDA/LSA), Doc2Vec , and Object Detection & Tracking . Drive agile practices including Sprint Planning, Resource Allocation, and Change Management . Communicate results and recommendations effectively to executive leadership and business teams. Mentor junior team members and foster a culture of continuous learning and innovation. Technical Skills Required: Programming: Python, SQL, Spark Machine Learning & AI: NLP, LLMs, Deep Learning, Computer Vision, Hybrid Recommenders Techniques: RAG, CAG, LLM-Finetuning, Statistical Modeling, AutoML, Doc2Vec Data Platforms: AWS (SageMaker, EC2), Databricks Databases: SQL, NoSQL, Neo4j, Cassandra, Vector DBs Visualization Tools: Tableau Certifications (Preferred): IBM Data Science Specialization Deep Learning Nanodegree (Udacity) SAFe® DevOps Practitioner Certified Agile Scrum Master Professional Competencies: Proven experience in team leadership, stakeholder management , and strategic planning . Strong cross-functional collaboration and ability to drive alignment across product, engineering, and analytics teams. Excellent problem-solving, communication, and decision-making skills. Ability to manage conflict resolution, negotiation , and performance optimization within teams.

Data Science, AI/MLPython, with experience MLlibrariesTensorFlow, PyTorch, Scikit-learn, XGBoost ML architecture patterns, data pipelines, distributed systems.AWS, Azure,GCP Docker, KubernetesMLOps, Spark, Hadoop, Hive,MLOps, model monitoring

Ciklum is looking for a Senior Data Scientist to join our team full-time in India. We are a custom product engineering company that supports both multinational organizations and scaling startups to solve their most complex business challenges. With a global team of over 4,000 highly skilled developers, consultants, analysts and product owners, we engineer technology that redefines industries and shapes the way people live. About the role: As a Senior Data Scientist, become a part of a cross-functional development team working for A healthcare technology company that provides platforms and solutions to improve the management and access of cost-effective pharmacy benefits. Our technology helps enterprise and partnership clients simplify their businesses and helps consumers save on prescriptions. Our client is a leader in SaaS technology for healthcare, They offer innovative solutions with integrated intelligence on a single enterprise platform that connects the pharmacy ecosystem. With their expertise and modern, modular platform, our partners use real-time data to transform their business performance and optimize their innovative models in the marketplace. Responsibilities: Development of prototype solutions, mathematical models, algorithms, machine learning techniques, and robust analytics to support analytic insights and visualization of complex data sets Work on exploratory data analysis so you can navigate a dataset and come out with broad conclusions based on initial appraisals Provide optimization recommendations that drive KPIs established by product, marketing, operations, PR teams, and others Interacts with engineering teams and ensures that solutions meet customer requirements in terms of functionality, performance, availability, scalability, and reliability Work directly with business analysts and data engineers to understand and support their use cases Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions Drive innovation by exploring new experimentation methods and statistical techniques that could sharpen or speed up our product decision-making processes Cross-trains other team members on technologies being developed, while also continuously learning new technologies from other team members Contribute to unit’s activities and community building, participate in conferences, and provide excellence in exercise and best practices Requirements: We know that sometimes, you can’t tick every box. We would still love to hear from you if you think you’re a good fit! 5+ years of development of Data Science solutions with a proven track record of leveraging analytics to drive significant business impact Bachelor's/Master's degree in Mathematics, Statistics, Computer Science, Operations Research, Econometrics or related field Proven ability to relate and solve business problems through machine learning and statistics 4+ years of experience applying various machine learning techniques: regression, classification, clustering, dimensional reduction, time series prediction, and/or outlier detection, recommendation systems Understanding of advantages and drawbacks of machine learning algorithms as well as their usage constraints including performance 4+ years of experience in Python development of machine learning solutions and statistical analysis: Pandas, SciPy, Scikit-learn, XGBoost, LightGBM, and/or statsmodels, imbalanced-learn libraries and ML libraries like scikit-learn, TensorFlow, PyTorch, data wrangling and visualization (e.g., Pandas, NumPy, Matplotlib, Seaborn Experience in working with large-scale datasets, including time series and healthcare data Experience with NLP, deep learning and GenAI Experience diving into data to consider hidden patterns and conducting error analysis 2+ years experience in data visualization: Power BI, Tableau, and/or Python libraries like Matplotlib and Seaborn Experience with SQL for data processing, data manipulation, sampling, reporting 3+ years experience creating/maintaining of OOP Machine Learning solutions Understanding of CRISP-ML(Q) / TDSP concept 1+ year of experience with MLOps: integration of reliable Machine Learning Pipelines in Production, Docker, containerization, orchestration 2+ years of experience with Clouds (AWS, Azure, GCP) and Clouds AI And ML Services(e.g. Amazon Sage Maker, Azure ML) Excellent time and project management skills, with the ability to manage detailed work and communicate project status effectively to all levels Desirable: Probability Theory & Statistics knowledge and intuition as well as understanding of Mathematics behind Machine Learning 1+ year of experience in Deep Learning solution development with Tensorflow or PyTorch libraries Data Science / Machine Learning certifications, or research experience with papers being published Experience with Kubernetes Experience with Databricks, Snowflake platforms 1+ year of BigData experience, i.e. Hadoop / Spark Experience with No-SQL, and/or columnar/graph databases What`s in it for you? Care: your mental and physical health is our priority. We ensure comprehensive company-paid medical insurance, as well as financial and legal consultation Tailored education path: boost your skills and knowledge with our regular internal events (meetups, conferences, workshops), Udemy license, language courses and company-paid certifications Growth environment: share your experience and level up your expertise with a community of skilled professionals, locally and globally Opportunities: we value our specialists and always find the best options for them. Our Resourcing Team helps change a project if needed to help you grow, excel professionally, and fulfil your potential Global impact: work on large-scale projects that redefine industries with international and fast-growing clients Welcoming environment: feel empowered with a friendly team, open-door policy, informal atmosphere within the company and regular team-building events About us: India is a strategic growth market for Ciklum. Be a part of a big story created right now. Let’s grow our delivery center in India together! Boost your skills and knowledge: create and innovate with like-minded professionals — all of that within a global company with a local spirit and start-up soul. Supported by Recognize Partners and expanding globally, we will engineer the experiences of tomorrow! Be bold, not bored! Interested already? We would love to get to know you! Submit your application. We can’t wait to see you at Ciklum.

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Experience : 3.00 + years Salary : USD 2222-2592 / month (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Contract for 3 Months(40 hrs a week/160 hrs a month) (*Note: This is a requirement for one of Uplers' client - PvX Partners) What do you need for this opportunity? Must have skills required: Gaming, CAC, LTV, ROAS, Scikit-learn, UA Metrics, Data Science, Python, SQL PvX Partners is Looking for: Data Scientist – ROAS Forecasting Location: Remote Experience: 3–4 years Company: PvX Partners About PvX Partners PvX Partners is a global leader in performance marketing for mobile games and apps. We combine deep domain expertise with cutting-edge AI to optimize user acquisition campaigns for some of the world’s most innovative gaming and app companies. Our data intelligence platform leverages advanced machine learning to analyze performance signals, benchmark outcomes, and forecast returns, helping clients scale profitably and outperform their competition. At PvX, we value entrepreneurial spirit, creativity, and a proactive mindset. Join us and be part of a team that pushes boundaries at the intersection of technology, data, and marketing. The Role We are looking for a Data Scientist with 3–4 years of hands-on experience to drive development of forecasting models for Return on Ad Spend (ROAS) across gaming and consumer app companies. This is a high-impact role where you will analyze large-scale marketing and monetization datasets, develop predictive models, and create evaluation frameworks to guide investment decisions. You’ll work closely with product, engineering, and finance teams to translate business goals into robust, data-driven solutions. If you’re passionate about performance marketing, forecasting models, and enjoy solving problems that are both technical and strategic—this role is for you. You Will Build predictive models to forecast monthly ROAS over key time horizons (e.g., M1, M3, M6, M12) using historical cohort performance data. Identify and incorporate leading indicators such as CPI, CTR, early retention (Day 1–Day 7), and channel mix, and lagging indicators such as cumulative revenue, payback curves, and seasonal trends. Own the end-to-end modeling workflow: cohort creation, feature engineering, model development, backtesting, and deployment. Develop model evaluation frameworks to assess prediction quality over time—using metrics like MAPE, RMSE, and directionality accuracy. Build scenario-based tools that help stakeholders understand upside/downside impacts of marketing spend on long-term returns. Customize modeling approaches across game genres, monetization strategies (IAP vs IAA), and geographies—adapting to different client contexts. Collaborate with internal product, engineering, and client-facing teams to translate forecasts into actionable investment decisions. Document assumptions clearly and drive continuous improvements to model performance based on real-world feedback and new data. You Need 3–4 years of experience building and deploying machine learning models, preferably in marketing, gaming, or consumer tech domains. Solid understanding of ROAS, CAC, LTV, and related UA metrics—ideally with experience working with attribution data (MMPs like Appsflyer, Adjust, etc.). Proficiency in Python and common ML libraries (e.g., scikit-learn, XGBoost, Prophet, PyMC3, or LightGBM). Experience in building and maintaining end-to-end data pipelines using SQL, Airflow, or similar orchestration tools. Strong statistical intuition and experience with model evaluation techniques (e.g., cross-validation, backtesting, MAPE/RMSE). High degree of ownership, adaptability, and willingness to work across multiple client contexts with varied problem statements. Bonus points for familiarity with monetization models (IAP vs IAA), channel-level performance dynamics (Meta, Google, Unity, Applovin, etc.), and ROAS decay curves Engagement Type: 3 Month Fulltime Contract Job Type: Contract Location: Remote Working time: 10:00 AM to 7:00 PM Interview Process: 3 Rounds How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!