657 Xgboost Jobs - Page 25

Job Requisition ID # 25WD85491 Position Overview We are looking for an experienced Principal Software Engineer to join our platform team focusing on AI/ML Platform (AMP). This team builds and maintains central components to fast track the development of new ML/AI models such as model development studio, feature store, model serving and model observability. The ideal candidate would have a background in ML Ops, Data engineering and DevOps with the experience of building high scale deployment architectures and observability. As an important contributor to our engineering team, you will help shape the future of our AI/ML capabilities, delivering solutions that inspire value for our organization. You will report directly to an Engineering Manager, and you will be based in Pune. Responsibilities System design: You will design, implement and manage software systems for the AI/ML Platform and orchestrate the full ML development lifecycle for the partner teams Mentoring: Spreading your knowledge, sharing best practices and doing design reviews to step up the expertise at the team level Multi-cloud architecture: Define components which leverages strengths from multiple cloud platforms (e.g., AWS, Azure) to optimize performance, cost, and scalability AI/ML observability: You will build systems for monitoring performance of AI/ML models and find insights on the underlying data such as drift detection, data fairness/bias and anomalies ML Solution Deployment: You will develop tools for building and deploying ML artefacts in production environments and facilitating a smooth transition from development to deployment Big Data Management: Automate and orchestrate tasks related to managing big data transformation and processing and build large-scale data stores for ML artifacts Scalable Services: Design and implement low-latency, scalable prediction, and inference services to support the diverse needs of our users Cross-Functional Collaboration: Collaborate across diverse teams, including machine learning researchers, developers, product managers, software architects, and operations, fostering a collaborative and cohesive work environment End-to-end ownership: You will take the end-to-end ownership of the components and work with other engineers in the team including design, architecture, implementation, rollout and onboarding support to partner teams, production on-call support, testing/verification, investigations etc Minimum Qualifications Educational Background: Bachelor’s degree in Computer Science or equivalent practical experience Experience: Over 8 years of experience in software development and engineering, delivering production systems and services Prior experience of working with MLOps team at the intersection of the expertise across ML model deployments, DevOps and data engineering Hands-on skills: Ability to fluently translate the design into high quality code in golang, python, Java Knowledge of DevOps practices, containerization, orchestration tools such as CI/CD, Terraform, Docker, Kubernetes, Gitops Demonstrate knowledge of distributed data processing frameworks, orchestrators, and data lake architectures using technologies such as Spark, Airflow, iceberg/ parquet formats Prior collaborations with Data science teams to deploy their models, setting up ML observability for inference level monitoring Exposure for building RAG based applications by collaborating with other product teams, Data scientists/AI engineers Demonstrate creative problem-solving skills with the ability to break down problems into manageable components Knowledge of Amazon AWS and/or Azure cloud for solutioning large scale application deployments Excellent communication and collaboration skills, fostering teamwork and effective information exchange Preferred Qualifications Experience in integrating with third party vendors Experience in latency optimization with the ability to diagnose, tune, and enhance the efficiency of serving systems Familiarity with tools and frameworks for monitoring and managing the performance of AI/ML models in production (e.g., MLflow, Kubeflow, TensorBoard) Familiarity with distributed model training/inference pipelines using (KubeRay or equivalent) Exposure to leveraging GPU computing for AI/ML workloads, including experience with CUDA, OpenCL, or other GPU programming tools, to significantly enhance model training and inference performance Exposure to ML libraries such as PyTorch, TensorFlow, XGBoost, Pandas, and ScikitLearn Learn More About Autodesk Welcome to Autodesk! Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made. We take great pride in our culture here at Autodesk – our Culture Code is at the core of everything we do. Our values and ways of working help our people thrive and realize their potential, which leads to even better outcomes for our customers. When you’re an Autodesker, you can be your whole, authentic self and do meaningful work that helps build a better future for all. Ready to shape the world and your future? Join us! Salary transparency Salary is one part of Autodesk’s competitive compensation package. Offers are based on the candidate’s experience and geographic location. In addition to base salaries, we also have a significant emphasis on discretionary annual cash bonuses, commissions for sales roles, stock or long-term incentive cash grants, and a comprehensive benefits package. Diversity & Belonging We take pride in cultivating a culture of belonging and an equitable workplace where everyone can thrive. Learn more here: https://www.autodesk.com/company/diversity-and-belonging Are you an existing contractor or consultant with Autodesk? Please search for open jobs and apply internally (not on this external site). Show more Show less

📢 Now Hiring: Data Science Researcher – Survey Analytics, MMM & Choice Modeling 📍 Location: Remote / Hybrid | Full-Time About the Role We're looking for a Data Science Researcher who brings statistical depth, curiosity, and a passion for real-world impact. This role is ideal for someone with a strong foundation in survey analytics , marketing mix modeling (MMM) , discrete choice modeling , and segmentation , and who wants to work at the intersection of consumer behavior and quantitative insight. If you have a Master’s in Statistics and 1+ year of hands-on experience working with consumer data, this could be the perfect place to build your career. What You’ll Be Doing 🔬 Advanced Survey & Consumer Analytics Analyze large-scale survey datasets to uncover behavioral drivers, consumer segments, and hidden insights Apply advanced statistical techniques: Latent Class Analysis , Bayesian methods , regression models, and segmentation algorithms 📊 Marketing & Choice Modeling Conduct Marketing Mix Modeling (MMM) to evaluate marketing ROI and attribution Lead Discrete Choice Modeling (DCM) projects to understand preference structures and simulate market response Translate findings into strategy-shaping insights for marketing and product teams 🛠️ Data Engineering & Experimentation Build and maintain robust data pipelines, ensuring clean integration of APIs and external data sources Merge survey data with other structured data (e.g., stock market or behavioral datasets) for multi-layered insights Run experiments to test hypotheses, forecast behavior, and optimize performance metrics 🤝 Cross-functional Collaboration Work alongside analysts, data scientists, marketers, and product teams to embed insights into decisions Present findings in clear, actionable formats for both technical and non-technical audiences Who We’re Looking For 🎓 Must-Have Master’s in Statistics (mandatory) 1+ year of experience in data analytics with a focus on survey data, MMM, DCM, or segmentation Strong hands-on skills in Python , R , SQL , and data visualization tools Familiarity with tools like Sawtooth , Bayesian networks , or XGBoost is a plus A natural storyteller with data, comfortable running experiments and finding signal in noise 🚀 Good to Have Exposure to high-frequency data (e.g., trading or behavioral datasets) Experience working with consumer research teams or market research datasets Familiarity with cloud platforms like AWS, GCP, or Azure Compensation 💰 INR 15 LPA (fixed) + performance-linked bonus 🌍 Remote-friendly, collaborative environment with high research autonomy Why This Role Stands Out You'll work on real data, real impact — from understanding why consumers choose what they do, to helping improve marketing ROI, to segmenting audiences in smarter ways. No fluff, just great problems and the freedom to solve them your way. 📨 Interested? Apply now or message us directly. Know someone perfect for this? Tag them below. Show more Show less

Job Description Job summary: Financial Institutions routinely use models for a broad range of activities including analyzing business strategies, informing business decisions, identifying and measuring risk, valuing exposures or instruments, hedging derivative positions, conducting stress testing, assessing capital adequacy, managing clients assets, informing investment process, measuring compliance with internal limits, maintaining the formal control apparatus of the bank, meeting financial or regulatory reporting requirements and issuing public disclosures. Model Risk arises from the potential adverse consequences of making decisions based on incorrect or misused model outputs and reports, leading to financial loss, poor business decision making, or reputational damage. As part of the firm’s model risk management function, Model Risk Governance and Review Group (MRGR) is charged with developing model risk policy and control procedures, performing model validation activities, providing guidance on a model’s appropriate usage in the business context, evaluating ongoing model performance testing, and ensuring that model users are aware of the model strengths and limitations. Model manager roles within MRGR provide attractive career paths for model development and model validation quants in a dynamic setting working closely with Model Developers, Model Users, Risk and Finance professionals, where they act as key stakeholders on day-to-day model-related risk management decisions as well as conduct independent model validation of new and existing models. Core Responsibilities The successful candidate will be a member of the MRGR Group in Bengaluru covering all Data Science across all ex-trading applications of artificial intelligence and machine learning models across CIB: Engage in new model validation activities for all Data Science models in the coverage area - evaluate conceptual soundness of model specification; reasonableness of assumptions and reliability of inputs; fit for purpose; completeness of testing performed to support the correctness of the implementation; robustness of numerical aspects; suitability and comprehensiveness of performance metrics and risk measures associated with use of model. Conduct independent testing Perform additional model review activities ranging from proposed enhancements to existing models, extensions to scope of existing models. Liaise with Model Developers, Model Users, Risk and Finance professionals to provide oversight of and guidance on appropriate usage, controls around model restrictions & limitations, and findings for ongoing performance assessment & testing Maintain model risk control apparatus of the bank for the coverage area & serve as first point of contact Keep up with the latest developments in coverage area in terms of products, markets, models, risk management practices and industry standards Essential Skills, Experience, And Qualifications A Ph.D. or Master’s degree in a Data Science oriented field such as Data Science, Computer Science or Statistics, is required. Prior experience in following backgrounds (2-4+ years): Data Science, Quantitative Model Development, Model Validation or Technology focused on Data Science including hands on experience with building/testing machine learning models Strong understanding of Machine Learning / Data Science theory, techniques and tools including Transformers, Large Language Models, NLP, GANs, Deep Learning, OCR, XGBoost, and Reinforcement Learning Understanding of the machine learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop is an asset Proficiency in Python programming. Python machine learning library and ecosystem experience: Numpy Scipy Scikit-learn Theano TensorFlow Keras PyTorch Pandas Excellent writing skills: previous experience in writing scientific text with the ability to describe evidence and present logical reasoning clearly. Strong communication skills and ability to interface with other functional areas in the bank on model-related issues Risk and control mindset: ability to ask incisive questions, converge on critical matters, assess materiality and escalate issues ABOUT US JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. About The Team Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success. Show more Show less

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Position Name ML Developer Taleo ID Position Level Staff Employment Type Permanent Number of Openings 1 Work Location Kochi, Chennai , Noida , Bangalore , Pune , Kolkata , TVM Position Details As part of EY GDS Assurance Digital, you will be responsible for leveraging advanced machine learning techniques to develop innovative, high-impact models and solutions that drive growth and deliver significant business value. You will be helping EY’s sector and service line professionals by developing analytics enabled solutions, integrating data science activities with business relevant aspects to gain insight from data. This is a full-time Machine Learning Developer role, responsible for building and deploying robust machine learning models to solve real-world business problems. You will be working on the entire ML lifecycle, including data analysis, feature engineering, model training, evaluation, and deployment. Requirements (including Experience, Skills And Additional Qualifications) A bachelor’s degree (BE/BTech/MCA & MBA) in Computer Science, Engineering, Information Systems Management, Accounting, Finance or a related field with adequate industry experience. Technical Skills Requirements Develop and implement machine learning models, including regression, classification (e.g., XGBoost, Random Forest), and clustering techniques. Conduct exploratory data analysis (EDA) to uncover insights and trends within data sets. Apply dimension reduction techniques to improve model performance and interpretability. Utilize statistical models to design and implement effective business solutions. Evaluate and validate models to ensure robustness and reliability. Should have solid background in Python Familiarity with Time Series Forecasting. Basic experience with cloud platforms such as AWS, Azure, or GCP. Exposure to ML Ops tools and practices (e.g., MLflow, Airflow, Docker) is a plus Additional skill requirements: Proficient at quickly understanding complex machine learning concepts and utilizing technology for tasks such as data modeling, analysis, visualization, and process automation. Skilled in selecting and applying the most suitable standards, methods, tools, and frameworks for specific ML tasks and use cases. Capable of collaborating effectively within cross-functional teams, while also being able to work independently on complex ML projects. Demonstrates a strong analytical mindset and systematic approach to solving machine learning challenges. Excellent communication skills, able to present complex technical concepts clearly to both technical and non-technical audiences. What we look for A Team of people with commercial acumen, technical experience, and enthusiasm to learn new things in this fast-moving environment. An opportunity to be a part of market-leading, multi-disciplinary team of 7200 + professionals, in the only integrated global assurance business worldwide. Opportunities to work with EY GDS Assurance practices globally with leading businesses across a range of industries What working at EY offers At EY, we’re dedicated to helping our clients, from startups to Fortune 500 companies — and the work we do with them is as varied as they are. You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees, and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer: Support, coaching and feedback from some of the most engaging colleagues around Opportunities to develop new skills and progress your career The freedom and flexibility to handle your role in a way that’s right for you About EY As a global leader in assurance, tax, transaction, and advisory services, we’re using the finance products, expertise, and systems we’ve developed to build a better working world. That starts with a culture that believes in giving you the training, opportunities, and creative freedom to make things better. Whenever you join, however long you stay, the exceptional EY experience lasts a lifetime. And with a commitment to hiring and developing the most passionate people, we’ll make our ambition to be the best employer by 2020 a reality. If you can confidently demonstrate that you meet the criteria above, please contact us as soon as possible. Join us in building a better working world. Apply now EY provides equal employment opportunities to applicants and employees without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today. Show more Show less

Experience Required - 2-5 years Skillset - Must Have Languages & Frameworks: - Python (Pandas, NumPy, Sklearn, TensorFlow, Keras, Pytorch, Tkinter, Selenium, Beautiful soup, regular expressions, Flask), R Programming, MySQL, Analytics, Data Crawling, Flask API, Statistical Modelling, Visualization. Proficient in a t least a few of the following: Regression, Bayesian methods, Tree-based learners, SVM, RF, XgBoost, Time Series Modeling, Clustering Problem-solving: Ability to break the problem into small parts and apply relevant techniques to drive required outcomes. Experience with classical ML algorithms and its underline mathematics for data patterns and profiling. Experience working with Hyper-parameter optimisation, feature engineering, feature selection, calibration of models and benchmarking performance via AUC/Gini, Capture rates, K-S and other relevant metrics Should be strong in Data Structures and Algorithms. Should be able to do code complexity analysis/optimisation. Should be able to read research papers and pick ideas to quickly reproduce research in the most comfortable Deep Learning library. Good Verbal and Written communication skills Good To Have Exposure to Production Deployment of ML models Exposure to Deep learning technologies like Computer Vision and NLP. Exposure to Cloud Technologies like AWS or Azure Cloud. Exposure to deployment tools like Docker and Kubernetes Exposure to Big Data Technologies like Hadoop, Spark, Hive etc. Responsibilities - To provide expertise on multiple phases of a ML Project/research lifecycle from design, implementation, optimisation and support. Analyse real world problems and identify AI and ML solutions Explore and visualise data to gain an understanding, and then identify differences in data distribution that could affect performance in the real world Verifying data quality, and/or ensuring it via data cleaning Find available online datasets that could be used for training Generate Synthetic data and augmentation pipelines Define validation strategies Train and retrain Models and tune their hyper parameters wherever required Fine tune pertained models via transfer learning. Design & Develop high-quality products using python, ML Libraries Show more Show less

What we're looking for: At least 5 years of experience in designing & building AI applications for customer and deploying them into production. Software engineering experience in building Secure, scalable and performant applications for customers Experience with Document extraction using AI, Conversational AI, Vision AI, NLP or Gen AI Design, develop, and operationalize existing ML models by fine tuning, personalizing it Evaluate machine learning models and perform necessary tuning Develop prompts that instruct LLM to generate relevant and accurate responses Collaborate with data scientists and engineers to analyze and preprocess datasets for prompt development, including data cleaning, transformation, and augmentation Conduct thorough analysis to evaluate LLM responses, iteratively modify prompts to improve LLM performance Hands on customer experience with RAG solution or fine tuning of LLM model Build and deploy scalable machine learning pipelines on GCP or any equivalent cloud platform involving data warehouses, machine learning platforms, dashboards or CRM tools Experience working with the end-to-end steps involving but not limited to data cleaning, exploratory data analysis, dealing outliers, handling imbalances, analyzing data distributions (univariate, bivariate, multivariate), transforming numerical and categorical data into features, feature selection, model selection, model training and deployment Proven experience building and deploying machine learning models in production environments for real life applications Good understanding of natural language processing, computer vision or other deep learning techniques Expertise in Python, Numpy, Pandas and various ML libraries (e.g., XGboost, TensorFlow, PyTorch, Scikit-learn, LangChain) Familiarity with Google Cloud or any other Cloud Platform and its machine learning services Excellent communication, collaboration, and problem-solving skills Good to Have Google Cloud Certified Professional Machine Learning or TensorFlow Certified Developer certifications or equivalent Experience of working with one or more public cloud platforms - namely GCP, AWS or Azure Experience with AutoML and vision techniques Master’s degree in statistics, machine learning or related fields Show more Show less

If you are looking for a career at a dynamic company with a people-first mindset and a deep culture of growth and autonomy, ACV is the right place for you! Competitive compensation packages and learning and development opportunities, ACV has what you need to advance to the next level in your career. We will continue to raise the bar every day by investing in our people and technology to help our customers succeed. We hire people who share our passion, bring innovative ideas to the table, and enjoy a collaborative atmosphere. Who We Are ACV is a technology company that has revolutionized how dealers buy and sell cars online. We are transforming the automotive industry. ACV Auctions Inc. (ACV), has applied innovation and user-designed, data driven applications and solutions. We are building the most trusted and efficient digital marketplace with datasolutions for sourcing, selling and managing used vehicles with transparency and comprehensive insights that were once unimaginable. We are disruptors of theindustry and we want you to join us on our journey. ACV’s network of brands includes ACV Auctions, ACV Transportation, ClearCar, MAX Digital and ACV Capital within its Marketplace Products, as well as, True360 and Data Services. ACV Auctions is opening its new India Development Center in Chennai, India, and we’re looking for talented individuals to join our team. As we expand our platform, we’re offering a wide range of exciting opportunities across various roles. At ACV, we put people first and believe in the principles of trust and transparency. If you are looking for an opportunity to work with the best minds in the industry and solve unique business and technology problems? Look no further! Join us in shaping the future of the automotive marketplace! At ACV we focus on the Health, Physical, Financial, Social and Emotional Wellness of our Teammates and to support this we offer industry leading benefits and wellness programs. What You Will Do Successful candidates will demonstrate excellent skill and maturity, be self-motivated as well as team-oriented, and have the ability to support the development and implementation of end-to-end ML-enabled software solutions to meet the needs of internal stakeholders. Those who will excel in this role will be those who listen with an ear to the overarching goal, not just the immediate concern that started the query. They will be able to show their recommendations are contextually grounded in an understanding of the practical problem, the data, and theory as well as what product and software solutions are feasible and desirable. The Core Responsibilities Of This Role Are Leading a team of machine learning engineers to build, automate, deploy and scale ML models and pipelines in production. Enact ML and software development best practices for the team to follow. Monitoring performance and microservice health status of models in production. Partner with external stakeholders to prioritize, scope, and deliver ML solutions Perform additional duties as assigned. What You Will Need Graduate education in a computationally intensive domain. 7+ years of prior relevant work or lab experience in ML projects/research 2+ years as tech lead or team management experience Advanced proficiency with Python and SQL (BigQuery/MySQL). Experience with building scalable REST APIs (Flask, FastAPI) Experience with building data pipelines (Airflow, Kubeflow, sklearn pipelines, etc.) Extensive knowledge of ML frameworks and libraries like Feast, XGBoost, PyTorch etc. Familiarity with cloud platforms and tools for scalable ML operations (e.g., AWS, GCP, Kubernetes). Preferred Qualifications Experience with ML model development lifecycles Prior contributions to data architecture or software architecture projects Our Values Trust & Transparency | People First | Positive Experiences | Calm Persistence | Never Settling At ACV, we are committed to an inclusive culture in which every individual is welcomed and empowered to celebrate their true selves. We achieve this by fostering a work environment of acceptance and understanding that is free from discrimination. ACV is committed to being an equal opportunity employer regardless of sex, race, creed, color, religion, marital status, national origin, age, pregnancy, sexual orientation, gender, gender identity, gender expression, genetic information, disability, military status, status as a veteran, or any other protected characteristic. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires reasonable accommodation, please let us know. Show more Show less

Job Description: As a Senior Data and Applied Scientist, you will work with Pattern's Data Science team to curate and analyze data, and apply machine learning models and statistical techniques to solve business problems across the organization. Most of your work will revolve around logistics and operations. What you’ll do: Design, build, and maintain predictive machine learning models and simulations to optimize solutions across Pattern. Communicate potential model improvements, data needs, and opportunities across relevant business units and developer teams. Continuously optimize the quality of our machine learning models. Conduct research to integrate new data sources, innovate in feature engineering, fine-tune algorithms, and enhance data pipelines for robust model performance. Analyze large datasets to extract actionable insights that guide business decisions. Work closely with data science teams across different regions (US and India), ensuring seamless collaboration and knowledge sharing. Follow code standards and best practices. Perform root cause analysis to determine accuracy defects and drive improvements. What we’re looking for: Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Economics, or a related field. 2-6 years of industry experience in building and deploying machine learning solutions and simulations. 1-3 years of industry experience in logistics/operations. Understanding of linear programming, integer programming, and nonlinear programming Excellent communication skills (written and verbal) across departments with different levels of machine learning knowledge. Strong data manipulation and programming skills in Python and SQL, and hands-on experience with libraries such as Pandas, NumPy, Scikit-Learn, XGBoost. Strong problem-solving skills and an ability to analyze complex data. In-depth expertise in a range of machine learning and statistical techniques, such as linear and tree-based models, along with understanding of model evaluation metrics. Experience with Git, AWS, and deep learning models is advantageous. Pattern is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Show more Show less

Company Description Syngenta is one of the world’s leading agriculture innovation company (Part of Syngenta Group) dedicated to improving global food security by enabling millions of farmers to make better use of available resources. Through world class science and innovative crop solutions, our 60,000 people in over 100 countries are working to transform how crops are grown. We are committed to rescuing land from degradation, enhancing biodiversity and revitalizing rural communities. A diverse workforce and an inclusive workplace environment are enablers of our ambition to be the most collaborative and trusted team in agriculture. Our employees reflect the diversity of our customers, the markets where we operate and the communities which we serve. No matter what your position, you will have a vital role in safely feeding the world and taking care of our planet. To learn more visit: www.syngenta.com Job Description Purpose Be integral part of the P&S Data Science team that applies technical expertise in data management, data science, machine learning, artificial intelligence, and automation to design, build, deploy, and maintain solutions across multiple countries. Work with project teams and SMEs to understand business requirements and develop appropriate data and AI/ML solutions. Contribute solutions with explorative, predictive- or prescriptive models, utilizing optimization, simulation, and machine learning techniques to existing and new projects. Work independently to build applications for data collection and processing, exploration and visualization, analysis, regression, classification, and generation as required by the project and business teams. Accountabilities Develop and implement complex statistical models, machine learning algorithms, and data mining techniques to extract insights from large datasets. Lead data science projects from conception to completion, defining scope, methodology, and deliverables. Collaborate with business leaders to translate data insights into actionable strategies and recommendations. Guide and mentor junior data scientists, fostering their professional development and technical skills. Contribute to the design and improvement of data architecture, pipelines, and storage solutions. Stay current with the latest advancements in data science and introduce new techniques or technologies to the organization. Establish and maintain standards for data quality, documentation, and ethical use of data. Present complex findings to both technical and non-technical audiences, including executive leadership. Address complex business challenges using data-driven approaches and creative solutions. Improve the efficiency and scalability of data processing and model deployment. Develop deep knowledge in Syngenta’s P&S operations to better contextualize data insights. Own the design, build, and deploy process including collaboration with users and multi-disciplinary teams to fulfil the user, business and technical requirements. Qualifications Required Knowledge & Technical Skills Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related discipline (or equivalent practical experience). Understanding of ETL processes and data pipeline design. Required development skills: Data Science – TensorFlow Scikit-learn, SciPy, NumPy, Pandas, XGBoost, Keras, etc. Programming – Python with pytorch and tensorflow Data – SQL, EDA, Descriptive and Predictive analysis, visualization Preferred additional skills: Web services – RESTful APIs and API testing, JSON, etc. Front end – JavaScript, Flask, React, Node.js, Vue, Django, or other. Tools – Git, npm, pip, Heroku, or other tools. Knowledge and hands-on experience supervised and unsupervised ML using Logistic/multi-variate regression, Gradient Boosting, Decision Trees, Neural Network, Random Forest, Support Vector Machine, Naive Bayes, Time Series, Optimization, etc. Preference for proven experience in adapting algorithms to required models - Regression, Decision Trees, Random Forests, LLM. Preference for experience in production and supply domain: production planning, supply chain, logistics, track and trace, CRM, etc. Preference for experience in Deep Learning model development in agriculture, supply chain or related domains. Documentation of documentation of APIs, models, and operational manuals (Markdown, etc.). Must be able to work on end to end activities from design, development and deployment Required Experience Previous internship, placement, or project experience in data engineering, data science, software development, or a related field. Required 2 years experience of building data science projects using AI/ML models. Exposure to cloud platforms such as AWS, Azure, Google Cloud, or Data Bricks (preferred but not essential). Additional Information Note: Syngenta is an Equal Opportunity Employer and does not discriminate in recruitment, hiring, training, promotion or any other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, gender identity, marital or veteran status, disability, or any other legally protected status. Follow us on: Twitter & LinkedIn https://twitter.com/SyngentaAPAC https://www.linkedin.com/company/syngenta/ India page https://www.linkedin.com/company/70489427/admin/ Show more Show less

Job Title: Consultant I/ II – Analytics Location: Ahmedabad or Gurgaon (Hybrid) Job Type: Full-Time About The Role We are looking for a Consultant I or II – Analytics to join our growing team and drive direct marketing performance through data-driven insights. In this role, you will work on end-to-end analytics tasks — from building predictive models and segmentations to uncovering actionable insights and preparing client-ready presentations. This is an exciting opportunity to make an impact on the direct marketing strategies for leading brands in the US. Key Responsibilities Build predictive models and segmentation frameworks to support marketing initiatives Target the top performing segments for the upcoming direct marketing campaigns Conduct post-campaign analysis, ad-hoc deep dives, and performance reporting Translate business problems into analytical approaches and actionable solutions Prepare clear, concise client-facing decks and present findings to business audiences Deliver high-quality, accurate, and error-free analytical outputs Skills & Qualifications 2-6 years of experience in analytics with a BE/ B.Tech or MBA/ PGDM/ MSc/ ME/ M.Tech degree Strong hands-on skills in Python/R, SAS, SQL, MS Excel, and MS PowerPoint (prior experience in SAS is preferred but not mandatory) Solid understanding and experience of machine learning techniques such as linear/logistic regression, decision trees, random forests, XGBoost, and customer segmentation Excellent communication skills with the ability to present complex technical concepts to business stakeholders Strong attention to detail, self-motivation, and a continuous learning mindset Why Join Us Be part of impactful marketing analytics projects for dynamic brands Opportunity to work in a collaborative, growth-oriented environment Flexible hybrid work setup (Ahmedabad or Gurgaon locations) Show more Show less

About Hakkoda Hakkoda, an IBM Company, is a modern data consultancy that empowers data driven organizations to realize the full value of the Snowflake Data Cloud. We provide consulting and managed services in data architecture, data engineering, analytics and data science. We are renowned for bringing our clients deep expertise, being easy to work with, and being an amazing place to work! We are looking for curious and creative individuals who want to be part of a fast-paced, dynamic environment, where everyone’s input and efforts are valued. We hire outstanding individuals and give them the opportunity to thrive in a collaborative atmosphere that values learning, growth, and hard work. Our team is distributed across North America, Latin America, India and Europe. If you have the desire to be a part of an exciting, challenging, and rapidly-growing Snowflake consulting services company, and if you are passionate about making a difference in this world, we would love to talk to you!. We are seeking an exceptional and highly motivated Lead Data Scientist with a PhD in Data Science, Computer Science, Applied Mathematics, Statistics, or a closely related quantitative field, to spearhead the design, development, and deployment of an automotive OEM’s next-generation Intelligent Forecast Application. This pivotal role will leverage cutting-edge machine learning, deep learning, and statistical modeling techniques to build a robust, scalable, and accurate forecasting system crucial for strategic decision-decision-making across the automotive value chain, including demand planning, production scheduling, inventory optimization, predictive maintenance, and new product introduction. The successful candidate will be a recognized expert in advanced forecasting methodologies, possess a strong foundation in data engineering and MLOps principles, and demonstrate a proven ability to translate complex research into tangible, production-ready applications within a dynamic industrial environment. This role demands not only deep technical expertise but also a visionary approach to leveraging data and AI to drive significant business impact for a leading automotive OEM. Role Description Strategic Leadership & Application Design: Lead the end-to-end design and architecture of the Intelligent Forecast Application, defining its capabilities, modularity, and integration points with existing enterprise systems (e.g., ERP, SCM, CRM). Develop a strategic roadmap for forecasting capabilities, identifying opportunities for innovation and the adoption of emerging AI/ML techniques (e.g., generative AI for scenario planning, reinforcement learning for dynamic optimization). Translate complex business requirements and automotive industry challenges into well-defined data science problems and technical specifications. Advanced Model Development & Research: Design, develop, and validate highly accurate and robust forecasting models using a variety of advanced techniques, including: Time Series Analysis: ARIMA, SARIMA, Prophet, Exponential Smoothing, State-space models. Machine Learning: Gradient Boosting (XGBoost, LightGBM), Random Forests, Support Vector Machines. Deep Learning: LSTMs, GRUs, Transformers, and other neural network architectures for complex sequential data. Probabilistic Forecasting: Quantile regression, Bayesian methods to capture uncertainty. Hierarchical & Grouped Forecasting: Managing forecasts across multiple product hierarchies, regions, and dealerships. Incorporate diverse data sources, including historical sales, market trends, economic indicators, competitor data, internal operational data (e.g., production schedules, supply chain disruptions), external events, and unstructured data. Conduct extensive exploratory data analysis (EDA) to identify patterns, anomalies, and key features influencing automotive forecasts. Stay abreast of the latest academic researchand industry advancements in forecasting, machine learning, and AI, actively evaluating and advocating for their practical application within the OEM. Application Development & Deployment (MLOps): Architect and implement scalable data pipelines for ingestion, cleaning, transformation, and feature engineering of large, complex automotive datasets. Develop robust and efficient code for model training, inference, and deployment within a production environment. Implement MLOps best practices for model versioning, monitoring, retraining, and performance management to ensure the continuous accuracy and reliability of the forecasting application. Collaborate closely with Data Engineering, Software Development, and IT Operations teams to ensure seamless integration, deployment, and maintenance of the application. Performance Evaluation & Optimization: Define and implement rigorous evaluation metrics for forecasting accuracy (e.g., MAE, RMSE, MAPE, sMAPE, wMAPE, Pinball Loss) and business impact. Perform A/B testing and comparative analyses of different models and approaches to continuously improve forecasting performance. Identify and mitigate sources of bias and uncertainty in forecasting models. Collaboration & Mentorship: Work cross-functionally with various business units (e.g., Sales, Marketing, Supply Chain, Manufacturing, Finance, Product Development) to understand their forecasting needs and integrate solutions. Communicate complex technical concepts and model insights clearly and concisely to both technical and non-technical stakeholders. Provide technical leadership and mentorship to junior data scientists and engineers, fostering a culture of innovation and continuous learning. Potentially contribute to intellectual property (patents) and present findings at internal and external conferences. Qualifications Education: PhD in Data Science, Computer Science, Statistics, Applied Mathematics, Operations Research, or a closely related quantitative field. Experience: 5+ years of hands-on experience in a Data Scientist or Machine Learning Engineer role, with a significant focus on developing and deploying advanced forecasting solutions in a production environment. Demonstrated experience designing and developing intelligent applications, not just isolated models. Experience in the automotive industry or a similar complex manufacturing/supply chain environment is highly desirable. Technical Skills: Expert proficiency in Python (Numpy, Pandas, Scikit-learn, Statsmodels) and/or R. Strong proficiency in SQL. Machine Learning/Deep Learning Frameworks: Extensive experience with TensorFlow, PyTorch, Keras, or similar deep learning libraries. Forecasting Specific Libraries: Proficiency with forecasting libraries like Prophet, Statsmodels, or specialized time series packages. Data Warehousing & Big Data Technologies: Experience with distributed computing frameworks (e.g., Apache Spark, Hadoop) and data storage solutions (e.g., Snowflake, Databricks, S3, ADLS). Cloud Platforms: Hands-on experience with at least one major cloud provider (Azure, AWS, GCP) for data science and ML deployments. MLOps: Understanding and practical experience with MLOps tools and practices (e.g., MLflow, Kubeflow, Docker, Kubernetes, CI/CD pipelines). Data Visualization: Proficiency with tools like Tableau, Power BI, or similar for creating compelling data stories and dashboards. Analytical Prowess: Deep understanding of statistical inference, experimental design, causal inference, and the mathematical foundations of machine learning algorithms. Problem Solving: Proven ability to analyze complex, ambiguous problems, break them down into manageable components, and devise innovative solutions. Preferred Qualifications Publications in top-tier conferences or journals related to forecasting, time series analysis, or applied machine learning. Experience with real-time forecasting systems or streaming data analytics. Familiarity with specific automotive data types (e.g., telematics, vehicle sensor data, dealership data, market sentiment). Experience with distributed version control systems (e.g., Git). Knowledge of agile development methodologies. Soft Skills Exceptional Communication: Ability to articulate complex technical concepts and insights to a diverse audience, including senior management and non-technical stakeholders. Collaboration: Strong interpersonal skills and a proven ability to work effectively within cross-functional teams. Intellectual Curiosity & Proactiveness: A passion for continuous learning, staying ahead of industry trends, and proactively identifying opportunities for improvement. Strategic Thinking: Ability to see the big picture and align technical solutions with overall business objectives. Mentorship: Desire and ability to guide and develop less experienced team members. Resilience & Adaptability: Thrive in a fast-paced, evolving environment with complex challenges. Benefits Health Insurance Paid leave Technical training and certifications Robust learning and development opportunities Incentive Toastmasters Food Program Fitness Program Referral Bonus Program Hakkoda is committed to fostering diversity, equity, and inclusion within our teams. A diverse workforce enhances our ability to serve clients and enriches our culture. We encourage candidates of all races, genders, sexual orientations, abilities, and experiences to apply, creating a workplace where everyone can succeed and thrive. Ready to take your career to the next level? 🚀 💻 Apply today👇 and join a team that’s shaping the future!! Hakkoda is an IBM subsidiary which has been acquired by IBM and will be integrated in the IBM organization. Hakkoda will be the hiring entity. By Proceeding with this application, you understand that Hakkoda will share your personal information with other IBM subsidiaries involved in your recruitment process, wherever these are located. More information on how IBM protects your personal information, including the safeguards in case of cross-border data transfer, are available here. Show more Show less

Company Description Silverpush is at the forefront of AI-powered video advertising, delivering sophisticated ad solutions that empower brands to achieve impactful campaigns within a privacy-centric environment. Operating across 30+ countries, we specialize in creating contextually relevant advertising experiences that drive genuine engagement and conversion. Our commitment to innovation and technological advancement enables us to navigate the evolving digital landscape, providing tools necessary to connect with audiences globally. We are dedicated to fostering a culture of creativity and excellence, driving the future of ad tech. Role Description This is a full-time on-site role for a Data Scientist, located in Gurgaon. The ideal candidate will combine strong technical expertise with an AI-driven mindset, leveraging both traditional data science methods and cutting-edge AI tools to drive business impact. This role requires someone who can work independently while collaborating effectively across cross-functional teams to solve complex business problems. Key Responsibilities Analyze complex datasets to identify trends, patterns, and correlations, and extract actionable insights that can inform strategic decisions. Design and build predictive models using statistical and machine learning techniques (e.g., regression, classification, XGBoost, clustering). Research and develop analysis and forecasting and optimization methods across ads performance, content performance, and live experiments. Build and maintain automated data pipelines and analytical workflows Research and prototype using cutting-edge LLM technologies and generative AI to unlock new opportunities in personalization, targeting, and automation. Stay current with emerging AI technologies and evaluate their potential application to business problems Communicate complex findings to non-technical audiences through compelling visualizations and presentations Provide strategic recommendations based on data-driven insights to influence key business decisions Design and execute A/B tests and experiments to measure impact of business initiatives Work with engineering teams to productise models and ensure scalable deployment Maintain code quality standards and follow best practices for version control and documentation Optimize model performance and monitor deployed solutions for accuracy and reliability Ideal Candidate Profile 3+ years of experience in Data Science, ideally in advertising or media-related domains. Degree in a quantitative discipline (e.g., Statistics, Computer Science, Mathematics, Masters in DS). Deep experience working with large-scale structured and unstructured data. Strong foundation in machine learning and statistical modeling. Familiar with building and deploying models in production (basic MLOps knowledge). Comfortable with NLP and computer vision, and interested in applying LLMs to real-world use cases. Familiarity with generative AI tools and prompt engineering for analytical workflows Excellent communication skills, with the ability to explain complex concepts to non-technical stakeholders. Strong problem-solving skills and ability to work independently Technical Skills Languages & Tools : Python, PySpark, SQL ML Techniques : Regression, Classification, Clustering, Decision Trees, Random Forests, XGBoost, SVM LLM Tech : Familiarity with tools like OpenAI, Hugging Face, LangChain, and prompt engineering Data Infrastructure : ETL tools, Postgres, BigQuery/Snowflake, S3/GCP Statistical Analysis : A/B testing, experiment design, causal inference Show more Show less

Who we are Wayfair’s Advertising business is rapidly expanding, adding hundreds of millions of dollars in profits to Wayfair. We are building Sponsored Products, Display & Video Ad offerings that cater to a variety of Advertiser goals while showing highly relevant and engaging Ads to millions of customers. We are evolving our Ads Platform to empower advertisers across all sophistication levels to grow their business on Wayfair at a strong, positive ROI and are leveraging state of the art Machine Learning techniques. The Advertising Optimization & Automation Science team is central to this effort. We leverage machine learning and generative AI to streamline campaign workflows, delivering impactful recommendations on budget allocation, target Return on Ad Spend (tROAS), and SKU selection. Additionally, we are developing intelligent systems for creative optimization and exploring agentic frameworks to further simplify and enhance advertiser interactions. We are looking for Machine Learning Scientists to join the Advertising Optimization & Automation Science team. In this role, you will be responsible for the development of budget, tROAS and SKU recommendations and other machine learning capabilities supporting our ads business. You will work closely with other scientists, as well as members of our internal Product and Engineering teams, to apply your engineering and machine learning skills to solve some of our most impactful and intellectually challenging problems to directly impact Wayfair’s revenue. What you’ll do Design, build, deploy and refine large-scale machine learning models and algorithmic decision-making systems that solve real-world problems for customers Work cross-functionally with commercial stakeholders to understand business problems or opportunities and develop appropriately scoped analytical solutions Collaborate closely with various engineering, infrastructure, and machine learning platform teams to ensure adoption of best-practices in how we build and deploy scalable machine learning services Identify new opportunities and insights from the data (where can the models be improved? What is the projected ROI of a proposed modification?) Be obsessed with the customer and maintain a customer-centric lens in how we frame, approach, and ultimately solve every problem we work on. What you’ll need 3+ years of industry experience with a Bachelor/ Master’s degree or minimum of 1-2 years of industry experience with PhD in Computer Science, Mathematics, Statistics, or related field. Proficiency in Python or one other high-level programming language Solid hands-on expertise deploying machine learning solutions into production Strong theoretical understanding of statistical models such as regression, clustering and machine learning algorithms such as decision trees, neural networks, etc. Strong written and verbal communication skills Intellectual curiosity and enthusiastic about continuous learning Nice to have Experience with Python machine learning ecosystem (numpy, pandas, sklearn, XGBoost, etc.) and/or Apache Spark Ecosystem (Spark SQL, MLlib/Spark ML) Familiarity with GCP (or AWS, Azure), machine learning model development frameworks, machine learning orchestration tools (Airflow, Kubeflow or MLFlow) Experience in information retrieval, query/intent understanding, search ranking, recommender systems etc. Experience with deep learning frameworks like PyTorch, Tensorflow, etc. Show more Show less

Company Description Nykaa is a digitally native, consumer-tech company that offers a wide range of beauty, personal care and fashion products. Since its inception in 2012, Nykaa has disrupted the beauty retail market in India and captured the hearts of millions of customers. Besides offering engaging and educational content, we have diversified our offerings through other online platforms like Nykaa Fashion, Nykaa Man, and Superstore. Role: This is a full-time on-site role for a Machine Learning Engineer/Scientist in Bengaluru. As a Machine Learning Engineer/Scientist, you will design and deploy machine learning models to solve complex business problems. You will be responsible for developing and implementing statistical and machine learning algorithms, managing large datasets, and working collaboratively with cross-functional teams. You will be working on the interesting problem areas such as Personalization, Customer Growth, Demand Forecasting & Inventory Management and other DS problems. Key Skills Minimum 3 years experience Strong background in statistics, machine learning and deep learning Expertise in pattern recognition, neural networks, and ML algorithms Proficiency in statistical tools, Python programming language along with ML libraries (Scikit-Learning, XGBoost and LightGBM etc) Exposure to DL frameworks such as Keras, Tensorflow and Pytorch Have a sound understanding of modeling pipelines, ML architecture and MLOps Excellent problem-solving skills and attention to detail Ability to work collaboratively in a fast-paced environment Experience with Causal Inference and Experimentation would be an advantage Experience in Consumer tech experience would be a plus Experience on Search, Ranking, Relevance, Recommendations is highly preferred Show more Show less

Skills: Python, TensorFlow, PyTorch, Scikit-learn, NLP, Pandas, NumPy, Data Visualization, About Us We are a growing tech company based in Ahmedabad, building AI-powered enterprise applications for the BFSI sector, government bodies, and e-Auction and ProcureToPay domains. Our platforms include eAuction, FinTech Applications, and procurement automationpowered by cutting-edge AI technologies. Requirements Final year student / recent graduate (Computer Science, IT, Data Science, etc.) Solid foundation in Python programming Academic or personal project experience in any ML framework (XGBoost preferred) Familiar with or eager to learn: Vector Databases (FAISS, Weaviate) LangChain / RAG framework Scrapy or web scraping tools Pandas, Numpy, Scikit-learn, Transformers Nice to Have Exposure to OpenAI API, HuggingFace, or LLM-based projects Interest in Finanance / eAuction / Procure To Pay / e-Governance domains Git or version control understanding What We Offer Chance to work upon the Live AI projects Performance-based full-time opportunity after internship A collaborative, growth-focused work culture Show more Show less

Job Description: Position: Senior Technical Specialist – Data Science Location: Chennai Experience: 8+ Years Domain Expertise: AI/ML, Data Science, Cloud, DevOps, and MLOps Education: B.E. (ECE), MBA (Big Data Analytics). Job Summary: We are seeking an experienced Senior Technical Specialist - Data Science to lead AI/ML initiatives, design scalable data-driven solutions, and drive innovation. The ideal candidate will have strong expertise in AI/ML, data engineering, cloud technologies (Azure), and MLOps, with experience in managing teams and delivering AI-powered solutions for business challenges. Key Responsibilities: • Lead and mentor a team of Data Scientists to develop and deploy AI/ML models. • Architect end-to-end Machine Learning & AI solutions for complex business problems. • Design and implement Generative AI applications, including RAG-based chatbots using LLMs, LangChain, and Azure OpenAI. • Build, deploy, and monitor MLOps pipelines using MLFlow, Kubeflow, and Azure MLOps. • Develop predictive modeling, NLP applications, and deep learning frameworks using TensorFlow, PyTorch, and BERT. • Conduct data analysis and visualization using Power BI, Tableau, Matplotlib, and Streamlit. • Work with DevOps teams to automate ML workflows, optimize cloud infrastructure, and enhance model scalability. • Collaborate with business teams to define AI strategy, data-driven insights, and process improvements. • Research and implement the latest advancements in AI/ML to improve model accuracy and efficiency. Required Skills & Expertise: • Programming: Python, PowerShell, Bash, Perl • Machine Learning & Deep Learning: SVM, KNN, XGBoost, TensorFlow, PyTorch, LSTM • NLP & Generative AI: Spacy, BERT, LangChain, LlamaIndex, LLOps • Data Visualization: Tableau, Power BI, Matplotlib, Streamlit • Cloud & MLOps: Azure ML Studio, Azure OpenAI, Docker, Jenkins, GitHub, MLFlow, ClearML • Database & Big Data: MS-SQL, Data Preprocessing, Feature Engineering Preferred Qualifications: • Azure Data Scientist Certification • HackerRank Python & SQL Certification • Udacity NLP & Deep Learning Certifications Show more Show less

Salary : 25 to 40 LPA Exp: 4 to 8 years Location :Noida/Gurugram/Bangalore Notice: Immediate to 30 days..!! Roles & responsibilities: 5+ years exp on Python , ML and Banking model development Interact with the client to understand their requirements and communicate / brainstorm solutions, model Development: Design, build, and implement credit risk model. Contribute to how analytical approach is structured for specification of analysis Contribute insights from conclusions of analysis that integrate with initial hypothesis and business objective. Independently address complex problems 3+ years exp on ML/Python (predictive modelling) . Design, implement, test, deploy and maintain innovative data and machine learning solutions to accelerate our business. Create experiments and prototype implementations of new learning algorithms and prediction techniques Collaborate with product managers, and stockholders to design and implement software solutions for science problems Use machine learning best practices to ensure a high standard of quality for all of the team deliverables Has experience working on unstructured data ( text ): Text cleaning, TFIDF, text vectorization Hands-on experience with IFRS 9 models and regulations. Data Analysis: Analyze large datasets to identify trends and risk factors, ensuring data quality and integrity. Statistical Analysis: Utilize advanced statistical methods to build robust models, leveraging expertise in R programming. Collaboration: Work closely with data scientists, business analysts, and other stakeholders to align models with business needs. Continuous Improvement: Stay updated with the latest methodologies and tools in credit risk modeling and R programming.

Position : AI / ML Engineer Job Type : Full-Time Location : Gurgaon, Haryana, India Experience : 2 Years Industry : Information Technology Domain : Demand Forecasting in Retail/Manufacturing Job Summary We are seeking a skilled Time Series Forecasting Engineer to enhance existing Python microservices into a modular, scalable forecasting engine. The ideal candidate will have a strong statistical background, expertise in handling multi-seasonal and intermittent data, and a passion for model interpretability and real-time insights. Key Responsibilities Develop and integrate advanced time-series models: MSTL, Croston, TSB, Box-Cox. Implement rolling-origin cross-validation and hyperparameter tuning. Blend models such as ARIMA, Prophet, and XGBoost for improved accuracy. Generate SHAP-based driver insights and deliver them to a React dashboard via GraphQL. Monitor forecast performance with Prometheus and Grafana; trigger alerts based on degradation. Core Technical Skills Languages : Python (pandas, statsmodels, scikit-learn) Time Series : ARIMA, MSTL, Croston, Prophet, TSB Tools : Docker, REST API, GraphQL, Git-flow, Unit Testing Database : PostgreSQL Monitoring : Prometheus, Grafana Nice-to-Have : MLflow, ONNX, TensorFlow Probability Soft Skills Strong communication and collaboration skills Ability to explain statistical models in layman terms Proactive problem-solving attitude Comfort working cross-functionally in iterative development environments Job Type: Full-time Pay: ₹400,000.00 - ₹800,000.00 per year Application Question(s): Do you have at least 2 years of hands-on experience in Python-based time series forecasting? Have you worked in retail or manufacturing domains where demand forecasting was a core responsibility? Are you currently authorized to work in India without sponsorship? Have you implemented or used ARIMA, Prophet, or MSTL in any of your projects? Have you used Croston or TSB models for forecasting intermittent demand? Are you familiar with SHAP for model interpretability? Have you containerized a forecasting pipeline using Docker and exposed it through a REST or GraphQL API? Have you used Prometheus and Grafana to monitor model performance in production? Work Location: In person Application Deadline: 05/06/2025 Expected Start Date: 05/06/2025

Use various statistical techniques like regression and classification tests to report on potential risk areas and perform statistical deep dives to enhance analysis. Build metrics around both statistical and practical significance by building compelling analytical arguments and statistical models. Draft clear and concise reports of the results of ongoing monitoring and special assessment projects and present results to Compliance organization 4+ years' experience in statistics, data science, decision science, or a related quantitative field Masters degree required 3+ years experience with fair lending-related testing, including the following techniques: BISG algorithm Feature/variable proxy testing Shapley or related model proxy testing Statistical significance model proxy testing Classical and non-parametric statistical techniques as applicable Knowledge of consumer lending Working knowledge of machine learning models, specifically tree models like XGboost. Excellent analytical and deep dive skills using data analysis and model building. SQL/SAS/Python Show more Show less

Experience : 5.00 + years Salary : INR 8000000-10000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Office (Gurugram) Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Sentilink) (*Note: This is a requirement for one of Uplers' client - A US-based, funded innovative identity and risk solutions provider organization) What do you need for this opportunity? Must have skills required: Communication Skill, Fintech, Machine Learning models leverage XGBoost and PyTorch, API Building, AWS Infrastructure ( Terraform, Docker ), Experience in handling large-scale data, Python/GO, AWS, Kubernetes, PostgreSQL A US-based, funded innovative identity and risk solutions provider organization is Looking for: Role: As a Senior Software Engineer, you will be responsible for our applications and its platform. You will work with the product and engineering team to build new products and enhance our existing suite of products. You have outstanding programming skills, you are proficient in our technology stack, and you can pick up new technologies quickly as we evolve. Technologies : Golang, Python, Opensearch, PostgreSQL (RDS), Docker, AWS technologies This is an in-office position, based on Gurugram, India. Responsibilities : You are the owner of one or more large sections of our codebase. Consistently delivers large systems involving one or more teams' contribution on time at a high level of quality Shapes broad architecture; ships multiple large services, complex libraries or major pieces of infrastructure Lead the technical direction provide guidance and set the technical direction for our team, ensuring alignment with project goals and industry best practices Consistently able to reduce the complexity of projects, services, and processes in order to increase efficiency of teams Code, test, debug, document, and maintain software applications using established coding standards and methodologies Partner with product management to drive agile delivery of both existing and new products based on project requirement Ensure new software meets quality standards by writing unit and end-to-end automated tests Work with product, data, and other stakeholders to analyze usage and product metrics to inform key strategic decisions Troubleshoot, debug, and resolve product issues as they arise Work cross functionally to resolve complex customer problems Ensure platform and services meet SLA requirements; on call rotation for production issues, along with the rest of engineering Requirements: 5+ years of software development experience building enterprise or consumer facing products Experience with building API based products using python, golang, or similar technologies Excellent analytical and problem solving skills, interpersonal skills, and a sense of humor (enjoy the journey) Familiarity with: RDBMS (e.g. postgres) and ability to write efficient queries with optimal structures; Docker and AWS technologies; fintech or financial services; scrum / agile development environment Engagement Model - Direct Hire on client Payroll Shift - 11 AM to 8 PM IST Mode of work - Onsite in Gurugram Interview Process - 4 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! Show more Show less

We are looking for an experienced Data Scientist with a strong background in Retail & E-commerce Analytics , particularly in integrating offline store data into analytics solutions. The ideal candidate will leverage General Analytics , AI/ML , and other advanced data science techniques to bridge the gap between online and offline retail data, enabling smarter business decisions and enhancing customer experiences across both channels. Responsibilities: Offline Store Data Analytics : Analyze and integrate offline store data (sales, foot traffic, inventory, etc.) with online data to provide a holistic view of customer behavior and sales trends. Use AI/ML models to optimize offline store performance by forecasting demand, inventory needs, and staffing levels based on historical data. Analyze the impact of offline marketing campaigns and promotions on in-store foot traffic and sales, using predictive analytics and machine learning. Develop models to predict store performance, taking into account various factors like location, weather, local events, and other external variables. Retail & E-commerce Analytics : Use machine learning algorithms and statistical analysis to understand and predict consumer behavior, both in-store and online. Build and maintain models for customer segmentation , personalized marketing , and sales forecasting for both e-commerce and brick-and-mortar stores. Identify key metrics for store performance and customer satisfaction, helping management teams optimize strategies for in-store and online experiences. AI/ML Implementation For Retail Optimization : Apply AI/ML techniques (e.g., classification , regression , clustering , time series forecasting ) to retail data, enabling actionable insights for improving product assortment, pricing, and promotions both online and offline. Develop demand forecasting models for offline stores , ensuring optimal stock levels based on predicted customer needs and sales trends. Use machine learning to enhance inventory management in offline stores by predicting inventory shortages and surplus. Data Integration & Visualization : Work with large datasets from both offline and online sources to clean, integrate, and analyze the data, ensuring data accuracy and consistency. Develop dashboards and visualizations using tools like Tableau , Power BI , or Google Data Studio to communicate key findings and business insights to stakeholders. Create reports that combine insights from offline and online channels, providing a unified view of retail operations. Campaign Performance Analysis : Use data science techniques to analyze the effectiveness of offline marketing campaigns and promotions on both in-store and online traffic, conversion rates, and sales. Evaluate customer engagement with offline campaigns, offering insights into how online and offline channels influence each other. Collaboration With Cross-Functional Teams : Work closely with retail managers, marketing teams, and IT teams to implement data-driven solutions that improve customer experience and business performance. Collaborate with product, marketing, and supply chain teams to optimize the omnichannel strategy , including aligning online and offline inventories and promotions. Key Technical Skills: Machine Learning & AI : Proficiency in Python or R for building and deploying AI/ML models such as random forests , XGBoost , SVM , and neural networks . Strong experience in applying predictive modeling , regression analysis , and time series forecasting to retail data, including demand forecasting and sales prediction. Familiarity with deep learning techniques (e.g., RNNs , LSTMs ) for more complex data patterns, if relevant. Retail & E-commerce Analytics : Experience in analyzing point-of-sale (POS) data , foot traffic data , and customer journey data for offline retail stores. Understanding of e-commerce KPIs and how they integrate with offline store performance metrics. Strong knowledge of inventory optimization , supply chain management , and how they relate to both online and offline retail operations. Big Data & Data Integration : Proficiency in handling and analyzing large datasets from multiple sources (online and offline) using SQL , NoSQL , and cloud platforms like AWS , GCP , or Azure . Ability to work with ETL processes to integrate data from multiple systems, ensuring high-quality data for analysis. Data Visualization & Reporting : Experience with Tableau , Power BI , Google Data Studio , or other visualization tools to present insights and actionable business recommendations. Strong communication skills to present complex findings to both technical and non-technical stakeholders. Statistical Analysis : Proficiency in statistical methods for hypothesis testing, segmentation analysis, and measuring the effectiveness of retail strategies and campaigns. Familiarity with advanced statistical techniques, including Bayesian methods , Monte Carlo simulations , and multivariate testing . Desired Qualifications: Bachelor’s or Master’s degree in Computer Science , Data Science , Statistics , Engineering , or a related field. 5+ years of experience in data science or analytics in the retail or e-commerce industry, with a focus on offline store performance . Proven experience in applying AI/ML models to solve real-world business problems, including demand forecasting, personalization, and campaign optimization. Familiarity with offline store data (sales, foot traffic, inventory) and how it integrates with e-commerce platforms . Strong understanding of the retail industry, particularly in optimizing performance across omnichannel environments (online and offline). 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About Ericsson Ericsson is a leading provider of telecommunications equipment and services to mobile and fixed network operators globally. Our innovative solutions empower individuals, businesses, and societies to explore their full potential in the Networked Society. We are seeking a highly skilled and experienced Data Scientist to join our dynamic team at Ericsson. As a Data Scientist, you will be responsible for leveraging advanced analytics and machine learning techniques to drive actionable insights and solutions for our telecom domain. This role requires a deep understanding of data science methodologies, strong programming skills, and proficiency in cloud-based environments. Key Responsibilities Develop and deploy machine learning models for various applications including chat-bot, XGBoost, random forest, NLP, computer vision, and generative AI. Utilize Python for data manipulation, analysis, and modeling tasks. Proficient in SQL for querying and analyzing large datasets. Experience with Docker and Kubernetes for containerization and orchestration of applications. Basic knowledge of PySpark for distributed computing and data processing. Collaborate with cross-functional teams to understand business requirements and translate them into analytical solutions. Deploy machine learning models into production environments and ensure scalability and reliability. Preferably have experience working with Google Cloud Platform (GCP) services for data storage, processing, and deployment. Qualifications Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field. A Master's degree or PhD is preferred. 8-12 years of experience in data science and machine learning roles, preferably within the telecommunications or related industry. Proven experience in model development, evaluation, and deployment. Strong programming skills in Python and SQL. Familiarity with Docker, Kubernetes, and PySpark. Solid understanding of machine learning techniques and algorithms. Experience working with cloud platforms, preferably GCP. Excellent problem-solving skills and ability to work independently as well as part of a team. Strong communication and presentation skills, with the ability to explain complex analytical concepts to non-technical stakeholders. Why join Ericsson? At Ericsson, you´ll have an outstanding opportunity. The chance to use your skills and imagination to push the boundaries of what´s possible. To build solutions never seen before to some of the world’s toughest problems. You´ll be challenged, but you won’t be alone. You´ll be joining a team of diverse innovators, all driven to go beyond the status quo to craft what comes next. What happens once you apply? Click Here to find all you need to know about what our typical hiring process looks like. Encouraging a diverse and inclusive organization is core to our values at Ericsson, that's why we champion it in everything we do. We truly believe that by collaborating with people with different experiences we drive innovation, which is essential for our future growth. We encourage people from all backgrounds to apply and realize their full potential as part of our Ericsson team. Ericsson is proud to be an Equal Opportunity Employer. learn more. Primary country and city: India (IN) || Noida Req ID: 767292 Show more Show less

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title And Summary Manager- Data Science Who is Mastercard? Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships, and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all. Our Team As consumer preference for digital payments continues to grow, ensuring a seamless and secure consumer experience is top of mind. Optimization Solutions team focuses on tracking of digital performance across all products and regions, understanding the factors influencing performance and the broader industry landscape. This includes delivering data-driven insights and business recommendations, engaging directly with key external stakeholders on implementing optimization solutions (new and existing), and partnering across the organization to drive alignment and ensure action is taken. Are you excited about Data Assets and the value they bring to an organization? Are you an evangelist for data-driven decision-making? Are you motivated to be part of a team that builds large-scale Analytical Capabilities supporting end users across 6 continents? Do you want to be the go-to resource for data science & analytics in the company? The Role Work closely with global optimization solutions team to architect, develop, and maintain advanced reporting and data visualization capabilities on large volumes of data to support data insights and analytical needs across products, markets, and services The candidate for this position will focus on Building solutions using Machine Learning and creating actionable insights to support product optimization and sales enablement. Prototype new algorithms, experiment, evaluate and deliver actionable insights. Drive the evolution of products with an impact focused on data science and engineering. Designing machine learning systems and self-running artificial intelligence (AI) software to automate predictive models. Perform data ingestion, aggregation, and processing on high volume and high dimensionality data to drive and enable data unification and produce relevant insights. Continuously innovate and determine new approaches, tools, techniques & technologies to solve business problems and generate business insights & recommendations. Apply knowledge of metrics, measurements, and benchmarking to complex and demanding solutions. Role Ensure that all AI solutions follow industry standards for data management and privacy, covering aspects like data collection, use, storage, access, retention, output, reporting, and quality at Mastercard. Take a practical approach to AI, simplifying complex technical requirements to align with stakeholders' needs. Collaborate with global stakeholders to gather necessary information and define business problems. Think creatively to link AI methodologies with real business challenges. Identify common use case patterns to promote scalable AI through reusable models and a microservice approach. Build AI/ML solutions using the latest advancements from industry and academia. Use both open and proprietary technologies to address business problems. Work effectively across teams and geographies, leveraging broader team expertise to achieve AI goals. Partner with technical teams to deploy solutions in production environments. Foster a culture of learning and continuous improvement in AI capabilities. All About You 8+ years in Data Science, with a focus on AI strategy, execution, and solution development from the ground up. A passion for AI, demonstrated through participation in competitions such as Kaggle. Preferred experience or familiarity with cybersecurity, fraud, and risk solutions, including: Deep learning algorithms, open-source tools, and statistical environments (Python, R, SQL). Big data platforms like Hadoop, Hive, Spark, and GPU clusters for deep learning. Classical machine learning techniques such as Logistic Regression, Decision Trees, K-Means, PCA, and Time Series models (ARIMA/ARMA). Deep learning techniques including Random Forest, GBM, Neural Networks (CNNs, LSTMs), and optimization techniques (Adam, Adagrad, etc.). Frameworks like TensorFlow, Keras, PyTorch, and XGBoost for production systems. Experience or exposure to collaboration tools like Confluence, Bitbucket, ALM, etc. Knowledge of the payments industry and experience with SAFe (Scaled Agile Framework) is a plus. Effectiveness Ability to manage assumptions and validate them with key stakeholders under tight deadlines, while keeping development on track. Strong problem-solving skills, with the ability to break down complex issues and apply the right AI techniques to solve them. Deep attention to detail, ensuring high confidence in developed solutions. Strong understanding of technical system architecture and interdependencies, anticipating challenges and proactively solving them. Core Capabilities Excellent written and verbal communication skills. Strong project management experience. Background in Computer Science. Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines. R-245889 Show more Show less

Job Title: AI Lead Engineer Location: Vapi, Gujarat Experience Required: 5+ Years Working Days: 6 Days a Week (Monday–Saturday) Industry Exposure: Manufacturing, Retail, Finance, Healthcare, life sciences or related field. Job Description: We are seeking a highly skilled and hands-on AI Lead to join our team in Vapi . The ideal candidate will have a proven track record of developing and deploying machine learning systems in real-world environments, along with the ability to lead AI projects from concept to production. You will work closely with business and technical stakeholders to drive innovation, optimize operations, and implement intelligent automation solutions. Key Responsibilities: Lead the design, development, and deployment of AI/ML models for business-critical applications. Build and implement computer vision systems (e.g., defect detection, image recognition) using frameworks like OpenCV and YOLO. Develop predictive analytics models (e.g., predictive maintenance, forecasting) using time series and machine learning algorithms such as XGBoost. Build and deploy recommendation engines and optimization models to improve operational efficiency. Establish and maintain robust MLOps pipelines using tools such as MLflow, Docker, and Jenkins. Collaborate with stakeholders across business and IT to define KPIs and deliver AI solutions aligned with organizational objectives. Integrate AI models into existing ERP or production systems using REST APIs and microservices. Mentor and guide a team of junior ML engineers and data scientists. Required Skills & Technologies: Programming Languages: Python (advanced), SQL, Bash, Java (basic) ML Frameworks: Scikit-learn, TensorFlow, PyTorch, XGBoost DevOps & MLOps Tools: Docker, FastAPI, MLflow, Jenkins, Git Data Engineering & Visualization: Pandas, Spark, Airflow, Tableau Cloud Platforms: AWS (S3, EC2, SageMaker – basic) Specializations: Computer Vision (YOLOv8, OpenCV), NLP (spaCy, Transformers), Time Series Analysis Deployment: ONNX, REST APIs, ERP System Integration Qualifications: B.Tech / M.Tech / M.Sc in Computer Science, Data Science, or related field. 6+ years of experience in AI/ML with a strong focus on product-ready deployments. Demonstrated experience leading AI/ML teams or projects. Strong problem-solving skills and the ability to communicate effectively with cross-functional teams. Domain experience in manufacturing, retail, or healthcare preferred. What We Offer: A leadership role in an innovation-driven team Exposure to end-to-end AI product development in a dynamic industry environment Opportunities to lead, innovate, and mentor Competitive salary and benefits package 6-day work culture supporting growth and accountability This is a startup environment but with good reputable company, We are looking for someone who can work Monday to Saturday and who can lead a team and generate new solutions and ideas and lead / manage the project effectively-- Please fill this given below form before applying https://forms.gle/8b3gdxzvc2JwnYfZ6 Show more Show less

Job Description: As a Senior Data and Applied Scientist, you will work with Pattern's Data Science team to curate and analyze data and apply machine learning models and statistical techniques to optimize advertising spend on ecommerce platforms. What you’ll do: Design, build, and maintain machine learning and statistical models to optimize advertising campaigns to improve search visibility and conversion rates on ecommerce platforms. Continuously optimize the quality of our machine learning models, especially for key metrics like search ranking, keyword bidding, CTR and conversion rate estimation Conduct research to integrate new data sources, innovate in feature engineering, fine-tuning algorithms, and enhance data pipelines for robust model performance. Analyze large datasets to extract actionable insights that guide advertising decisions. Work closely with teams across different regions (US and India), ensuring seamless collaboration and knowledge sharing. Dedicate 20% of time to MLOps for efficient, reliable model deployment and operations. What we’re looking for: Bachelor's or Master's in Data Science, Computer Science, Statistics, or a related field. 3-6 years of industry experience in building and deploying machine learning solutions. Strong data manipulation and programming skills in Python and SQL and hands-on experience with libraries such as Pandas, Numpy, Scikit-Learn, XGBoost. Strong problem-solving skills and an ability to analyze complex data. In depth expertise in a range of machine learning and statistical techniques such as linear and tree-based models along with understanding of model evaluation metrics. Experience with Git, AWS, Docker, and MLFlow is advantageous. Additional Pluses: Portfolio: An active Kaggle or Github profile showcasing relevant projects. Domain Knowledge: Familiarity with advertising and ecommerce concepts, which would help in tailoring models to business needs. Pattern is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Show more Show less