3397 Data Scientist Jobs - Page 22

About The Role We are seeking an innovative Data Scientist specializing in Natural Language Processing (NLP) to join our technology team in Bangalore. The ideal candidate will harness the power of language models and document extraction techniques to transform legal information into accessible, actionable insights for our clients. Responsibilities Develop and implement NLP solutions to automate legal document analysis and extraction Create and optimize prompt engineering strategies for large language models Design search functionality leveraging semantic understanding of legal documents Build document extraction pipelines to process unstructured legal text data Develop data visualizations using PowerBI and Tableau to communicate insights Collaborate with product and legal teams to enhance our tech-enabled services Continuously improve model performance and user experience Requirements Bachelor's degree in relevant field 1-5 years of professional experience in data science, with focus on NLP applications Demonstrated experience working with LLM APIs (e.g., OpenAI, Anthropic, ) Proficiency in prompt engineering and optimization techniques Experience with document extraction and information retrieval systems Strong skills in data visualization tools, particularly PowerBI and Tableau Excellent programming skills in Python and familiarity with NLP libraries Strong understanding of legal terminology and document structures (preferred) Excellent communication skills in English What We Offer Competitive salary and benefits package Opportunity to work at India's largest legal tech company Professional growth in the fast-evolving legal technology sector Collaborative work environment with industry experts Modern office located in Bangalore Flexible work arrangements Qualified candidates are encouraged to apply with a resume highlighting relevant experience with NLP, prompt engineering, and data visualization tools. Location : Bangalore, India Skills:- Machine Learning (ML), Data Science, Generative AI, Artificial Intelligence (AI), Natural Language Processing (NLP) and Large Language Models (LLM) tuning

ABOUT US aioneers is a digital first supply chain management consulting firm, headquartered in Germany. We use state of the art cloud data technology and decades of supply chain consulting experience to deliver innovative decision intelligence solutions to our customers. YOUR ROLE AT AIONEERS As a Senior Data Scientist, you will be a pivotal member of the data science team within aioneers. You will be leading the solution implementation of data science work streams within our supply chain analytics projects. Often the projects involve solving complex supply chain problems like demand forecasting, multi-echelon inventory optimization, production scheduling, intelligent order fulfillment, rough cut capacity planning (RCCP) etc. You will also provide technical guidance and mentorship junior data scientists in the team. You will own development and implementation of end-to-end life cycle of machine learning solutions from data modelling, feature engineering, ML solution structuring to MLOps process implementation of automated model serving You will play the role of a technology architect to design efficient MLOps process for large scale model deployments and high frequency servings using Azure data and ML services You will provide thought leadership to solution architects and project managers to come up with effective solution architecture for client s problems You will be building heuristics, Operations research techniques based (like linear programming and discrete optimization) solutions to solve optimization problems in supply chain space You will also lead the data engineering work activities within the projects to create required data models with features stores for ML implementations and post processing activities to make the outputs consumable for business use cases YOUR PROFILE We are looking for someone with 5+ years of relevant data science and machine learning experience in solving supply chain problems Data Science and Machine Learning Skills Understanding of statistical methods (e.g., regression, hypothesis testing) and optimization techniques like linear programming and mixed-integer programming for supply chain problems Proficiency in methods like ARIMA, SARIMAX, Prophet, or advanced techniques using neural networks (e.g., LSTMs, Temporal Fusion Transformer) Familiarity with supervised and unsupervised learning for classification (e.g., demand segmentation) and clustering (e.g., supplier categorization) Knowledge of CI/CD pipelines for ML, including retraining, deployment, and monitoring models using Azure DevOps or GitHub Actions Supply Chain Domain Knowledge: Seasoned expertise in demand forecasting using ML. Understanding the nuances of intermittent, erratic and lumpy demand patterns and how to solve them using ML techniques Knowledge of EOQ, reorder point models, safety stock modelling and inventory simulation techniques would be a plus Programming and Technical Skills Expertise in setting up end to end MLOps processes - model training, deployment, and tracking experiments Expertise in creating data pipelines for ETL processes and connecting supply chain data sources Proficiency in integrating ERP data from systems like SAP into Azure via connectors or APIs Deploying scalable ML models as APIs using AKS (Kubernetes) Expertise in handling large-scale supply chain datasets using Spark, Databricks, or Azure Synapse Advanced query skills in Azure SQL Database or Cosmos DB for real-time analytics Advanced proficiency in Python for ML modelling, data analysis, and libraries like Scikit-learn, PyTorch, TensorFlow Version control and automating deployments using Azure DevOps or GitHub Actions Ability to think through automation, pipeline design and other MLOps processes Conceptual and pragmatic knowledge of the concepts of data modelling, feature engineering, fine tuning machine learning models, statistical model validation Educational Background and Experience Engineering degree in computer science, informatics, data analytics and other relevant branches Affinity for new technologies and a drive for independent learning Affinity for an open feedback culture with flat hierarchies WHY AIONEERS At aioneers, we are building the next generation innovative solutions on supply chain technologies. What we can offer is a wonderful team culture, flexible work hours, respect for your ideas, open discussions / open door policies and attractive remuneration. Your results count and not the hours. You will have the chance to actively participate in the development and execution of innovative business strategies on an international scale. Apply for this job Apply for this job

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts. Job Category Data Job Details About Salesforce Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn t a buzzword it s a way of life. The world of work as we know it is changing and were looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforces core values at the heart of it all. Ready to level-up your career at the company leading workforce transformation in the agentic eraYou re in the right place! Agentforce is the future of AI, and you are the future of Salesforce. About the Company - We re Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. Leading with our core values, we help companies across every industry blaze new trails and connect with customers in a whole new way. And, we empower you to be a Trailblazer, too driving your performance and career growth, charting new paths, and improving the state of the world. If you believe in business as the greatest platform for change and in companies doing well and doing good you ve come to the right place. About the role We re looking for an experienced Data Scientist who will help us build marketing attribution, causal inference, and uplift models to improve the effectiveness and efficiency of our marketing efforts. This person will also design experiments and help us drive consistent approach to experimentation and campaign measurement to support a range of marketing, customer engagement, and digital use cases. This Lead Data Scientist brings significant experience in designing, developing, and delivering statistical models and AI/ML algorithms for marketing and digital optimization use cases on large-scale data sets in a cloud environment. They show rigor in how they prototype, test, and evaluate algorithm performance both in the testing phase of algorithm development and in managing production algorithms. They demonstrate advanced knowledge of statistical and machine learning techniques along with ensuring the ethical use of data in the algorithm design process. At Salesforce, Trust is our number one value and we expect all applications of statistical and machine learning models to adhere to our values and policies to ensure we balance business needs with responsible uses of technology. Responsibilities As part of the Marketing Effectiveness Data Science team within the Salesforce Marketing Data Science organization, develop statistical and machine learning models to improve marketing effectiveness - e.g., marketing attribution models, causal inference models, uplift models, etc. Develop optimization and simulation algorithms to provide marketing investment and allocation recommendations to improve ROI by optimizing spend across marketing channels. Own the full lifecycle of model development from ideation and data exploration, algorithm design and testing, algorithm development and deployment, to algorithm monitoring and tuning in production. Design experiments to support marketing, customer experience, and digital campaigns and develop statistically sound models to measure impact. Collaborate with other data scientists to develop and operationalize consistent approaches to experimentation and campaign measurement. Be a master in cross-functional collaboration by developing deep relationships with key partners across the company and coordinating with working teams. Constantly learn, have a clear pulse on innovation across the enterprise SaaS, AdTech, paid media, data science, customer data, and analytics communities. Required Skills 8+ years of experience designing models for marketing optimization such as multi-channel attribution models, customer lifetime value models, propensity models, uplift models, etc. using statistical and machine learning techniques. 8+ years of experience using advanced statistical techniques for experiment design (A/B and multi-cell testing) and causal inference methods for understanding business impact. Must have multiple, robust examples of using these techniques to measure effectiveness of marketing efforts and to solve business problems on large-scale data sets. 8+ years of experience with one or more programming languages such as Python, R, PySpark, Java. Expert-level knowledge of SQL with strong data exploration and manipulation skills. Experience using cloud platforms such as GCP and AWS for model development and operationalization is preferred. Must have superb quantitative reasoning and interpretation skills with strong ability to provide analysis-driven business insight and recommendations. Excellent written and verbal communication skills; ability to work well with peers and leaders across data science, marketing, and engineering organizations. Creative problem-solver who simplifies problems to their core elements. B2B customer data experience a big plus. Advanced Salesforce product knowledge is also a plus. Unleash Your Potential When you join Salesforce, you ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best , and our AI agents accelerate your impact so you can do your best . Together, we ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future but to redefine what s possible for yourself, for AI, and the world. Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactlyIt means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey.

About the Role We are looking for a highly motivated and skilled Senior Data Scientist or Data Scientist to join our team. The ideal candidate will have a strong background in data science, machine learning, and statistical analysis, with hands-on experience in Python and industry-standard libraries. You will be responsible for deriving actionable insights, building predictive models, and effectively communicating findings through data storytelling. Key Responsibilities Develop, implement, and optimize machine learning models for predictive analytics and decision-making. Work with structured and unstructured data to extract meaningful insights and patterns. Utilize Python and standard data science libraries such as NumPy, Pandas, SciPy, Scikit-Learn, TensorFlow, PyTorch, and Matplotlib for data analysis and model building. Design and develop data pipelines for efficient processing and analysis. Conduct exploratory data analysis (EDA) to identify trends and anomalies. Collaborate with cross-functional teams to integrate data-driven solutions into business strategies. Use data visualization and storytelling techniques to communicate complex findings to non-technical stakeholders. Stay updated with the latest advancements in machine learning and AI technologies. Required Qualifications 5+ years or 8+ years of hands-on experience in data science and machine learning. Strong proficiency in Python and relevant data science packages. Experience with machine learning frameworks such as TensorFlow, Keras, or PyTorch. Knowledge of SQL and database management for data extraction and manipulation. Expertise in statistical analysis, hypothesis testing, and feature engineering. Understanding of Marketing Mix Modeling is a plus. Experience in data visualization tools such as Matplotlib, Seaborn, or Plotly package Strong problem-solving skills and ability to work with large datasets. Excellent communication skills with a knack for storytelling using data. Preferred Qualifications Experience with cloud platforms such as AWS, Azure, or GCP. Knowledge of big data technologies like Hadoop, Spark, or Databricks. Exposure to NLP, computer vision, or deep learning techniques. Understanding of A/B testing and experimental design. Not the right fitLet us know youre interested in a future opportunity by clicking Introduce Yourself in the top-right corner of the page or create an account to set up email alerts as new job postings become available that meet your interest!

We are seeking a highly skilled Senior Data Scientist with experience in pricing optimization, pricing elasticity, and AWS SageMaker. The ideal candidate will have a strong foundation in Statistics and Machine Learning, with a particular focus on Bayesian modeling. As part of our Data Science team, you will work closely with clients to develop advanced pricing strategies using state-of-the-art tools and techniques, including AWS SageMaker, to optimize business outcomes. Experience : 5 to 7 Years Work Location : Hyderabad Key Responsibilities: Lead and contribute to the development of pricing optimization models, leveraging statistical and machine learning techniques to inform strategic decisions. Analyze pricing elasticity to predict consumer response to changes in price, helping clients maximize revenue and market share. Implement and deploy machine learning models using AWS SageMaker for scalable and efficient performance in a cloud environment. Utilize Bayesian modeling to support decision-making processes, providing insights into uncertainty and model predictions. Collaborate with cross-functional teams to integrate data-driven insights into business processes. Communicate complex results and findings in a clear and concise manner to both technical and non-technical stakeholders. Continuously explore and experiment with new modeling approaches and tools to improve accuracy and efficiency of pricing solutions. Bachelor s or Master s degree in Data Science, Statistics Mathematics Economics, or a related field. Advanced degrees preferred. 5+ years of hands-on experience in data science, with a focus on pricing optimization and elasticity mode

Job Summary: We are seeking a highly experienced Data Scientist with a strong foundation in ML/DL, experience in Computer Vision, with affinity towards upcoming technologies like Generative AI (GenAI) and Large Language Models (LLMs). The ideal candidate will lead and deploy cutting-edge AI solutions, bridging the gap between intelligent models and scalable backend architectures. Key Responsibilities: Design, develop, and deploy advanced Machine Learning and Deep Learning models for business-critical use cases. Build and optimize Computer Vision pipelines using models like YOLO, EfficientNet, or Transformer-based vision architectures. Integrate AI models into scalable backend services using Django, Flask, or FastAPI. Build robust RESTful APIs and manage data pipelines for AI workflows. Collaborate closely with frontend/backend engineers to bring AI features to production. Required Qualifications: Bachelor s/Master s degree in Computer Science, Artificial Intelligence, Data Science, or related fields. 8+ years of experience in building and deploying ML/DL models (time series, NLP, etc.). Proven expertise in Computer Vision (e.g., segmentation, detection, video analysis). Proficiency in Python, with frameworks like PyTorch, TensorFlow, OpenCV, and Hugging Face. Solid experience in backend frameworks: Django, Flask, or FastAPI, and building APIs for AI model inference. Familiarity with containerization (Docker), orchestration (Kubernetes), and cloud platforms (AWS, GCP, Azure). Exposure to MLOps tools and concepts (e.g., MLflow, Weights & Biases, CI/CD pipelines). Preferred Skills: Knowledge of LLMs (e.g., GPT, LLaMA, Mistral), agentic AI frameworks such as LangChain, AutoGPT is a plus.

Overview Synoptek We think globally, act locally. As a Managed Services Provider, Synoptek provides world-class strategic IT leadership and hyper-efficient IT operational support, enabling our global client-base to grow and transform their businesses. We are excited to have experienced continuous growth and in keeping with that momentum we are seeking to add talent to our team. When you partner with Synoptek, you engage with an ever-growing, ever-evolving IT organization that provides a high-caliber team, results growth, and clarity. Responsibilities Data Scientist This is an amazing opportunity to work within one of the fastest growing Managed Services Providers. We are a company with a heart and soul dedicated to the ongoing success and growth of our employees and continued business success of the customers we support. We foster a fun and connected environment with employee benefits extending beyond general compensation and into company sponsored events and an invested culture of learning. The Data Scientist is responsible for conducting end-to-end analysis, encompassing requirements, activities, and design. Additionally, the Data Analyst is responsible for developing analysis and reporting capabilities and implementing performance and quality control measures to drive continuous improvement. Role & Responsibilities: Should be able to code in Python and work with simple to complex SQL Work as independent contributor in building AI solutions using latest tech stack. Should be able to research, learn and implement latest models in AI and GenAI Identify, analyse, and interpret trends or patterns in complex datasets. Collaborate with team, to prioritize business and information needs. Serve as a consultant for clients nationwide. Identify and define process improvement opportunities. Excellent problem-solving ability and verbal communication. Experience Atleast 3 years of relevant experience in Building AI solutions. Proficiency in programming languages such as Python, FastAPI, SQL or PySpark(good to have) Experience in developing conversational AI or virtual assistant applications. Proven experience in building and deploying applications using LLMs like OpenAI GPT-4o, Claude, Llama, Grok, Gemini or similar Hands-on experience in building GenAI Applications. Good to have working experience in building Agentic AI applications. Familiarity with acquiring and managing huge and complex data from various sources, including structured and unstructured data sources. Extensive experience with Cloud platforms, particularly Microsoft Azure. Knowledge of natural language processing (NLP) and information retrieval Have knowledge and hands-on experience with LangChain Framework, Azure OpenAI, Azure AI Search Service, Indexing, and Embedding techniques Good to have Application development experience using AI models and API integrations. Hands-on experience in AI, ML and Deep Learning algorithms like Regression, Decision Trees, Neural networks Experience in working with Azure Cosmos DB, Azure Blobs, Azure Functions, and App Service Qualifications Education Bachelor’s degree in Computer Science, Information Technology or related field from an accredited college or university preferred In lieu of undergraduate degree, the ratio is 1:1 - meaning one year of college equals one year of work experience and vice versa Experience Customarily has at least 1 year(s) of job-related experience Familiarity with acquiring and managing data from various sources, including primary and secondary data sources. Skills/Attributes Synoptek core DNA behaviors: Clarity: Possesses excellent communication skills, makes a concentrated effort to speak the customers language. Ability to field questions with concise, well-constructed responses. OwnIT: Shows integrity, innovation, and accountability in completing daily assignments. Results: Solutions focused and driven to resolve conflict quickly and precisely. Proactively looks for opportunities to contribute to the company’s business goals. Growth: Willing to learn and ask questions. Constantly looking for new ways to improve yourself. Ability to adapt and grow in a fast-paced environment. Team: Embraces both customers and colleagues as team members. Ability to be flexible, respectful, engaged and collaborative. Capacity to identify, analyze, and interpret trends or patterns in complex datasets and propose solutions to business challenges. Strong verbal and written communication skills to collaborate with management, prioritize business needs, and work effectively as a consultant with clients. Working Conditions We live by the motto ‘work hard, play hard’ and strive to support our employees in both their professional and personal goals. We believe that by hiring the right people, leading process improvement, and leveraging technology, we achieve superior results. Work is performed primarily in an office or remote environment. May be subject to time constraints and tight deadlines. May require occasional travel. EEO Statement We are proud to be an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, veteran status, sexual orientation, gender identity, marital status, pregnancy, genetic information, or any other characteristic protected by law and will not be discriminated against on the basis of disability. It is our intention that all qualified applicants are given equal opportunity and that employment decisions be based on job-related factors.

Responsibilities: Lead and manage end-to-end data science projects, including project planning, scoping, budgeting, resource allocation, and timeline management. Collaborate with cross-functional teams, including data scientists, engineers, and business stakeholders, to define project requirements, deliverables, and milestones. Conduct project kick-off meetings, define project objectives, and establish clear project scopes and deliverables. Develop and maintain project plans, track progress, and provide regular updates to stakeholders, ensuring project milestones are met within the defined timeline. Identify and manage project risks, issues, and dependencies, implementing mitigation strategies and contingency plans as necessary. Coordinate and communicate project activities, ensuring alignment with organizational goals and objectives. Monitor project budget, resource utilization, and expenses, making necessary adjustments to optimize project performance and efficiency. Foster a collaborative and innovative work environment, promoting knowledge sharing and best practices within the data science team. Stay updated with industry trends, emerging technologies, and advancements in data science methodologies, and propose relevant process improvements or tool adoption. Provide leadership and mentorship to the data science team, facilitating their professional growth and development. Requirements: Bachelor's degree in computer science, Data Science, Statistics, or a related field. A master's degree is preferred. Proven experience (5+ years) in managing data science projects, preferably in a fast-paced and dynamic environment. Strong understanding of data science concepts, machine learning algorithms, and statistical modeling techniques. Proficient in project management methodologies, tools, and techniques. Excellent organizational and time management skills, with the ability to prioritize tasks and meet deadlines. Exceptional problem-solving and analytical abilities, with keen attention to detail. Excellent communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams and present complex concepts to non-technical stakeholders. Strong leadership skills, with the ability to motivate and inspire team members. Experience with data visualization tools, programming languages (e. g., Python, R), and big data technologies is a plus. Whatspp - 9886683329

Key Roles and Responsibilities of Position: Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making Design and implement data analysis and ML models, hypotheses, algorithms and experiments to support data-driven decision-making Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; to analyze data and uncover meaningful patterns, relationships, and trends Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation Research, study and stay updated in the domain of data science, machine learning, analytics tools and techniques etc.; and continuously identify avenues for enhancing analysis efficiency, accuracy and robustness Minimum Qualifications Bachelor’s degree in computer science, Operational research, Statistics, Applied mathematics, or in any other engineering discipline. 2+ years of hands-on experience in Python programming for data analysis, machine learning, and with libraries such as NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, PyTorch, NLTK, spaCy, and Gensim. 2+ years of experience with both supervised and unsupervised machine learning techniques. 2+ years of experience with data analysis and visualization using Python packages such as Pandas, NumPy, Matplotlib, Seaborn, or data visualization tools like Dash or PowerBI. 1+ years' experience in SQL programming language and relational databases. Preferred Qualifications An MS/PhD in Computer Science, Operational research, Statistics, Applied mathematics, or in any other engineering discipline. PhD strongly preferred. Experience working with Google Cloud Platform (GCP) services, leveraging its capabilities for ML model development and deployment. Experience with Git and GitHub for version control and collaboration. Besides Python, familiarity with one more additional programming language (e.g., C/C++/Java) Strong background and understanding of mathematical concepts relating to probabilistic models, conditional probability, numerical methods, linear algebra, neural network under the hood detail. Experience working with large language models such GPT-4, Google Gemini, Palm, Llama-2, etc. Excellent problem solving, communication, and data presentation skills. Key Roles and Responsibilities of Position: Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making Design and implement data analysis and ML models, hypotheses, algorithms and experiments to support data-driven decision-making Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; to analyze data and uncover meaningful patterns, relationships, and trends Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation Research, study and stay updated in the domain of data science, machine learning, analytics tools and techniques etc.; and continuously identify avenues for enhancing analysis efficiency, accuracy and robustness

Job Description Key Roles and Responsibilities of Position: Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making Design and implement data analysis and ML models, hypotheses, algorithms and experiments to support data-driven decision-making Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; to analyze data and uncover meaningful patterns, relationships, and trends Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation Research, study and stay updated in the domain of data science, machine learning, analytics tools and techniques etc.; and continuously identify avenues for enhancing analysis efficiency, accuracy and robustness Responsibilities Key Roles and Responsibilities of Position: Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making Design and implement data analysis and ML models, hypotheses, algorithms and experiments to support data-driven decision-making Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; to analyze data and uncover meaningful patterns, relationships, and trends Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation Research, study and stay updated in the domain of data science, machine learning, analytics tools and techniques etc.; and continuously identify avenues for enhancing analysis efficiency, accuracy and robustness Qualifications Minimum Qualifications Bachelor’s degree in computer science, Operational research, Statistics, Applied mathematics, or in any other engineering discipline. 2+ years of hands-on experience in Python programming for data analysis, machine learning, and with libraries such as NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, PyTorch, NLTK, spaCy, and Gensim. 2+ years of experience with both supervised and unsupervised machine learning techniques. 2+ years of experience with data analysis and visualization using Python packages such as Pandas, NumPy, Matplotlib, Seaborn, or data visualization tools like Dash or PowerBI. 1+ years' experience in SQL programming language and relational databases. Preferred Qualifications An MS/PhD in Computer Science, Operational research, Statistics, Applied mathematics, or in any other engineering discipline. PhD strongly preferred. Experience working with Google Cloud Platform (GCP) services, leveraging its capabilities for ML model development and deployment. Experience with Git and GitHub for version control and collaboration. Besides Python, familiarity with one more additional programming language (e.g., C/C++/Java) Strong background and understanding of mathematical concepts relating to probabilistic models, conditional probability, numerical methods, linear algebra, neural network under the hood detail. Experience working with large language models such GPT-4, Google Gemini, Palm, Llama-2, etc. Excellent problem solving, communication, and data presentation skills.

Position Overview: Here at ShyftLabs, we are looking for an experienced Data Scientist who can derive performance improvement and cost efficiency in our product through a deep understanding of the ML and infra system, and provide a data-driven insight and scientific solution. ShyftLabs is a growing data product company that was founded in early 2020, and works primarily with Fortune 500 companies. We deliver digital solutions built to help accelerate the growth of businesses in various industries, by focusing on creating value through innovation. Job Responsibilities: Data Analysis and Research: Analyzing a large dataset with queries and scripts, extracting valuable signals out of noise, and producing actionable insights into how we could complete and improve a complex ML and bidding system. Simulation and Modelling: Validating and quantifying the efficiency and performance gain from hypotheses through rigorous simulation and modelling. Experimentation and Causal Inference: Developing a robust experiment design and metric framework, and providing reliable and unbiased insights for product and business decision making. Basic Qualifications: Master's degree in a quantitative discipline or equivalent. 3+ years minimum professional experience. Distinctive problem-solving skills, good at articulating product questions, pulling data from large datasets and using statistics to arrive at a recommendation. Excellent verbal and written communication skills, with the ability to present information and analysis results effectively. Ability to build positive relationships within ShyftLabs and with our stakeholders, and work effectively with cross-functional partners in a global company. Statistics: Must have strong knowledge and experience in experimental design, hypothesis testing, and various statistical analysis techniques such as regression or linear models. Machine Learning: Must have a deep understanding of ML algorithms (i.e., deep learning, random forest, gradient boosted trees, k-means clustering, etc.) and their development, validation, and evaluation. Programming: Experience with Python, R, or other scripting language, and database language (e.g. SQL) or data manipulation (e.g. Pandas). We are proud to offer a competitive salary alongside a strong insurance package. We pride ourselves on the growth of our employees, offering extensive learning and development resources.

Position: LLM Engineer Experience: 5–9 Years Location: Remote Key Responsibilities: Design, develop, and optimize LLM-powered systems with a core focus on Retrieval-Augmented Generation (RAG) , prompt engineering, fine-tuning, and agent-based solutions. Lead the end-to-end development lifecycle of GenAI applications using LangChain / LangGraph , ensuring scalable and modular architecture. Own and maintain high-quality Python codebases , with a strong emphasis on reusable components, performance, and integration with vector databases or search engines used in RAG systems. Deploy and optimize solutions on cloud platforms (Azure, AWS, or GCP) using best practices in CI/CD, containerization, and cost optimization. Collaborate cross-functionally with product managers, SMEs, data scientists, and other engineers to gather requirements and deliver business-aligned AI solutions. Mentor junior engineers and guide best practices in working with LLMs and RAG pipelines. Stay up to date with the latest in LLM research, RAG frameworks, embeddings, vector stores , and transformer-based model capabilities to continuously enhance solution effectiveness. Required Skills: 5+ years of professional experience building machine learning systems and data-intensive applications. Minimum 1+ year of deep, hands-on experience with LLMs and Generative AI , including: Mandatory: Expertise in Retrieval-Augmented Generation (RAG) Prompt engineering and tuning LLM orchestration and agent-based systems Strong command of Python , with practical experience using LangChain or LangGraph in production environments. Solid understanding of vector databases (e.g., FAISS, Pinecone, Weaviate, Chroma) and embedding techniques . Experience in SQL and integrating structured/unstructured data with GenAI pipelines. Proven track record deploying AI applications on AWS, Azure, or GCP . Excellent communication and collaboration skills; ability to work with technical and non-technical stakeholders. Prior experience leading technical initiatives or mentoring team members is a strong plus.

Schaeffler is a dynamic global technology company and its success has been a result of its entrepreneurial spirit and long history of private ownership. Does that sound interesting to you? As a partner to all of the major automobile manufacturers, as well as key players in the aerospace and industrial sectors, we offer you many development opportunities. Your Key Responsibilities Research and define analytical models based on given data/information as part of analytical ad hoc feasibility cases, proofs of concepts or with a focus on software development towards deployable analytics solutions. Collaborate with internal and/or external clients to understand business requirements. Compile, sort and organize function-specific information and data in preparation for subsequent analyses. Conduct both routine and instant data cleaning and testing, identify and resolve data quality issues in cooperation with the team. Analyze data for instant feasibility cases and proofs of concepts. Actively contribute in the research and definition of analytical models that will be transferred in the products eventually. Your Qualifications Graduate Degree in Business Informatics, Applied Computer Science, Mathematics, Software Engineering, Machine Learning 3 to 5 years As a global company with employees around the world, it is important to us that we treat each other with respect and value all ideas and perspectives. By appreciating our differences, we inspire creativity and drive innovation. In this way, we contribute to sustainable value creation for our stakeholders and society as a whole. Together, we advance how the world moves. Exciting assignments and outstanding development opportunities await you because we impact the future with innovation. We look forward to your application. www.schaeffler.com/careers Your Contact Schaeffler Technology Solutions India Pvt. Ltd. Kalyani More For technical questions, please contact this email address: technical-recruiting-support-AP@schaeffler.com Keywords: Experienced; Engineer; Full-Time; Unlimited; Digitalization & Information Technology;

Roles & Responsibilities: Professional Skill: Business Analysis, Analytical Thinking, Problem Solving, Decision Making, Leadership, Managerial, Time Management, Domain Knowledge Work simplification - methods that maximize output while minimizing expenditure and cost. Analytics with Data - interprets data and turns it into information which can offer ways to improve a business Communication - Good verbal communication and interpersonal skills are essential for collaborating with customers Technical Skills: Python/Numpy, Seaborn, Pandas, Selenium, Beautiful Soup (basic), Spotfire, ML Libraries, RPA, R, Iron-Python, Html CSS, Javascript, SQL, HQL, Git/Gitlabee, Spark, Scala, Webservices, Spotfire/ Tableau, JIRA Tool Skill: Project management tools, Documentation tools, Modeling [wireframe] tools Database Skills: MsSQL, Postgres, MsAccess, Mongo DB Rigorous - The ability to analyse qualitative data quickly and rigorously Adaptability - Being able to adapt to changing environments and work processes Experience : Minimum 8 years of experience in Data Science / Preferable in Automobile Engineering Domain What we look from candidate who has matching skills on below. Key Skills: DAO - AI/ML, Automation, Python, big query. Project Management*, Agile, SDLC. Location : Chennai - Mahindra World City Campus. Work Mode : Hybrid

#Data Scientist #Data analysis #Retrieval-Augmented Generation (RAG) #Dataanalysis #EDA # #NumPy #scikit-learn #pandas #NLP #NLR #FAISS #AWS #BERT #Python #scikit Job Overview: • Build, train, and validate machine learning models for prediction, classification, and clustering to support NBA use cases. • Conduct exploratory data analysis (EDA) on both structured and unstructured data to extract actionable insights and identify behavioral drivers. • Design and deploy A/B testing frameworks and build pipelines for model evaluation and continuous monitoring. • Develop vectorization and embedding pipelines using models like Word2Vec, BERT, to enable semantic understanding and similarity search. • Implement Retrieval-Augmented Generation (RAG) workflows to enrich recommendations by integrating internal and external knowledge bases. • Collaborate with cross-functional teams (engineering, product, marketing) to deliver data-driven Next Best Action strategies. • Present findings and recommendations clearly to technical and non-technical stakeholders. Required Skills & Experience: • Strong programming skills in Python, including libraries like pandas, NumPy, and scikit-learn. • Practical experience with text vectorization and embedding generation (Word2Vec, BERT, SBERT, etc.). • Proficiency in Prompt Engineering and hands-on experience in building RAG pipelines using LangChain, Haystack, or custom frameworks. • Familiarity with vector databases (e.g., PostgreSQL with pgvector, FAISS, Pinecone, Weaviate). • Expertise in Natural Language Processing (NLP) tasks such as NER, text classification, and topic modeling. • Sound understanding of supervised learning, recommendation systems, and classification algorithms. • Exposure to cloud platforms (AWS, GCP, Azure) and containerization tools (Docker, Kubernetes) is a plus.

About the Role At Best NanoTech Academy , we’re building a next-generation learning platform focused on semiconductors, AI, and deep tech — and we believe data science sits at the heart of delivering a transformative learning experience. We’re looking for a Data Scientist who can help us uncover meaningful insights from learner behavior, content engagement, and platform analytics. Your work will directly influence how thousands of students across the world access knowledge, improve their skills, and succeed in the booming semiconductor and electronics sectors. Key Responsibilities Analyze user behavior, course engagement, and learner outcomes to improve platform performance Build real-time dashboards and data pipelines to track key metrics across the academy Develop predictive models to personalize content, forecast learner progress, and reduce drop-off Collaborate with marketing, content, and product teams to drive data-informed decisions Run A/B tests and implement data-backed recommendations to enhance user experience Explore AI/ML tools to bring automation and intelligent features into the learning journey Skills & Qualifications 2–5 years of experience in data science, preferably in edtech, analytics, or SaaS environments Strong proficiency in Python, R, SQL, and data visualization tools like Tableau, Power BI, or Looker Solid grasp of statistical modeling, hypothesis testing, and machine learning frameworks (e.g., scikit-learn, TensorFlow, Keras) Experience working with product data, marketing funnels, or learner engagement metrics Bonus: Experience with LMS platforms, education tech tools, or adaptive learning algorithms Be part of a vision-led startup transforming semiconductor workforce education across the globe

Key Roles and Responsibilities of Position: Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making Design and implement data analysis and ML models, hypotheses, algorithms and experiments to support data-driven decision-making Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; to analyze data and uncover meaningful patterns, relationships, and trends Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation Research, study and stay updated in the domain of data science, machine learning, analytics tools and techniques etc.; and continuously identify avenues for enhancing analysis efficiency, accuracy and robustness Minimum Qualifications Bachelor’s degree in computer science, Operational research, Statistics, Applied mathematics, or in any other engineering discipline. 2+ years of hands-on experience in Python programming for data analysis, machine learning, and with libraries such as NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, PyTorch, NLTK, spaCy, and Gensim. 2+ years of experience with both supervised and unsupervised machine learning techniques. 2+ years of experience with data analysis and visualization using Python packages such as Pandas, NumPy, Matplotlib, Seaborn, or data visualization tools like Dash or PowerBI. 1+ years' experience in SQL programming language and relational databases. Preferred Qualifications An MS/PhD in Computer Science, Operational research, Statistics, Applied mathematics, or in any other engineering discipline. PhD strongly preferred. Experience working with Google Cloud Platform (GCP) services, leveraging its capabilities for ML model development and deployment. Experience with Git and GitHub for version control and collaboration. Besides Python, familiarity with one more additional programming language (e.g., C/C++/Java) Strong background and understanding of mathematical concepts relating to probabilistic models, conditional probability, numerical methods, linear algebra, neural network under the hood detail. Experience working with large language models such GPT-4, Google Gemini, Palm, Llama-2, etc. Excellent problem solving, communication, and data presentation skills. Key Roles and Responsibilities of Position: Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making Design and implement data analysis and ML models, hypotheses, algorithms and experiments to support data-driven decision-making Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; to analyze data and uncover meaningful patterns, relationships, and trends Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation Research, study and stay updated in the domain of data science, machine learning, analytics tools and techniques etc.; and continuously identify avenues for enhancing analysis efficiency, accuracy and robustness

Are you a talented Data Scientist (includes AI/ML Researcher, AI/ML Engineer, Data Engineer, ML Ops Engineer, QA Engineer with AI/ML focus, NLP Engineer, LLM Engineer) either, Looking for your next big challenge working remotely OR Employed , but open to offers from elite US companies to work remotely? Submit your resume to our GlobalPros.ai’s, an exclusive community of the world’s top pre-vetted developers dedicated to precisely matching you with our US employers. Globlpros.ai is followed internationally by over 13,000 employers, agencies and the world’s top developers. We are currently searching for a full-time AI/ML developer (includes AI/ML Researcher, AI/ML Engineer, Data Engineer, Data Scientist, ML Ops Engineer, QA Engineer with AI/ML focus, NLP Engineer) to work remotely for our US employer clients. What We Offer: Competitive Compensation . Compensation is negotiable and commensurate with your experience and expertise. Pre-vetting so you’re 2x more likely to be hired . Recent studies by Indeed and LinkedIn show pre-vetted candidates like you are twice as likely to be hired. Shortlist competitive advantage . Our machine learning technology matches you precisely to job requirements and because your pre-vetted ensures you're shortlisted ahead of other candidates. Personalized career support . Free one-on-one career counseling and interview prep to help guarantee you succeed. Anonymity . If you’re employed but open to offers, your profile is anonymous and is not available on our website or otherwise online. When matched with our clients, your profile is anonymous until you agree to be interviewed. So there’s no risk in submitting your resume now. We're Looking For: Experience . Must have at least 3 years of experience . Role . AI/ML developer (includes AI/ML Researcher, AI/ML Engineer, Data Engineer, Data Scientist, ML Ops Engineer, QA Engineer with AI/ML focus, NLP Engineer) Skills . TensorFlow, PyTorch, Scikit-learn Python, Java, C++, R, AWS, Azure, GCP, (SQL, NoSQL, Hadoop, Spark, Docker, Kubernetes, AWS Redshift, Google BigQuery. Willing to work full-time . (40 hours per week) . Available for an hour of assessment testing . Being deeply-vetted with a data enhanced resume and matched precisely by our machine learning algorithms substantially increases the probability of being hired quickly, at higher compensation levels over unvetted candidates. It's your substantial competitive advantage in a crowded job market.

Exp- 5+ Years Location- Bangalore/Pune/Mumbai/Delhi NCR/Hyderabad Budget- Upto 30 LPA Required Skills Python: Hands-on experience with threading limitations and multi-process architecture. MySQL: Ability to integrate multiple data sources using MySQL. Strong coding knowledge and experience with several languages (e.g., R, SQL, JavaScript, Java, CSS, C++). Familiarity with statistical and data mining techniques (e.g., GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis). Experience with advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc

Responsibilities: ● You would be required to Identify, develop and implement the appropriate statistical techniques, algorithms and Deep learning / ML Models to create new, scalable solutions that address business challenges across industry domains. ● Define, develop, maintain and evolve data models, tools and capabilities. ● Communicate your findings to the appropriate teams through visualizations ● Collaborate and communicate findings to diverse stakeholders ● Provide solutions for but not limited to: Object detection/Image recognition, natural language processing, Sentiment Analysis, Topic Modeling, Concept Extraction, Recommender Systems, Text Classification, Clustering , Customer Segmentation & Targeting, Propensity Modeling, Churn Modeling, Lifetime Value Estimation, Forecasting, Modeling Response to Incentives, Marketing Mix Optimization, Price Optimization, Gen AI and LLMs. ● Ability to build, train and lead a team of data scientists. ● Follow/maintain an agile methodology for delivering on project milestones. ● Excellent oral, presentation, and written communication skills. ● Experience applying statistical ideas and methods to data sets to answer business problems. ● Mine and analyze data to drive optimization and improvement of product development, marketing techniques and business strategies. Tech Stack: ● Strong Python programming Knowledge- Data Science and Advanced Concepts like Abstract Class, Function Overloading + Overriding, Inheritance, Modular Programming and Reusability ● Cloud Experience in using Azure services, ● REST API using Flask or fastapi frameworks ● Good to have - Pyspark: Spark Dataframe Operations, SQL functions API, Parallel Execution Preferred Qualifications: ● Bachelors/ Masters/ PhD degree in Math, Computer Science, Information Systems, Machine Learning, Statistics, Applied Mathematics or related technical degree. ● 6 plus years total experience with minimum of 3 years of experience in a related position, as a data scientist building Predictive analytics, Computer Vision, and NLP solutions for various types of business problems. ● Advanced knowledge of statistical techniques, machine learning algorithms and deep learning frameworks like Tensorflow, Keras, Pytorch ● Programming background and expertise in building models using at least one of the following languages: Python, R , C, C++ Job Types: Full-time, Permanent Pay: From ₹1,500,000.00 per year Benefits: Flexible schedule Health insurance Paid sick time Paid time off Provident Fund Schedule: Day shift Ability to commute/relocate: Chennai, Tamil Nadu: Reliably commute or planning to relocate before starting work (Required) Application Question(s): What is your official NP? How strong would you rate yourself in Python on a scale of 10 Work Location: In person

Primary Skills: Data Science, AI/ML, GenAI, LLM, NLP, Any Cloud (Azure/AWS/GCP) Roles & Responsibilities: Develop custom data models and algorithms to apply to data sets. Developing and implementing advanced machine learning models to address complex problems. Clearly communicate findings and recommendations, data-driven insights to PMs and executives. Qualifications: Bachelors/Masters degree in Computer Science, Engineering, or a related technical field with minimum 5 years' experience. Experience in performing prompt engineering and fine-tuning of the AI/ML, GenAI, LLM models. Practical hands-on fine-tuning/transfer learning/optimization of the Transformer architecture-based Deep Learning models. Experience in NLP tools such as Word2Vec, TextBlob, NLTK, SpaCy, Gensim, CoreNLP, BERT, GloVe etc. Experience in AWS / Azure / GCP cloud and deploying the APIs using the latest frameworks like FastAPI/ gRPC etc. Experience in Docker for deploying the containers. Deployment of the ML models on the Kubernetes clusters Experience in NoSQL/SQL databases. Good programming skills in Python. Domain knowledge in Online Reputation management or experience in a product-based company (added advantage). Expertise in delivering end-to-end analytical solutions covering multiple technologies & tools to multiple business problems.

Job Title: Data Scientist (o9 Platform Experience) Location: Remote Experience: 4+ Years Employment Type: Full-time About the Role We are looking for an experienced Data Scientist with hands-on expertise in the o9 Solutions platform to join our dynamic and fast-paced team. As a Data Scientist, you will work closely with cross-functional teams to deliver data-driven insights and implement solutions that enhance business decision-making and planning. Required Skills and Qualifications Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Engineering, or a related field. Minimum of 4 years of experience in data science or analytics roles. Hands-on experience with the o9 Solutions platform in analytics, forecasting, or planning modules. Proficient in Python, R, SQL, and data visualization tools (e.g., Power BI, Tableau). Strong knowledge of statistical modeling, machine learning algorithms, and data preprocessing techniques. Experience working with cloud platforms like AWS, Azure, or GCP is a plus. Excellent problem-solving, communication, and collaboration skills. Ability to work independently in a fully remote environment.

About You You are an expert in applying advanced analytics to solve marketing and sales business problems. You are equally comfortable applying your knowledge to optimize marketing spend or working with sales to optimize trade spend. You are hands-on in your ability to build models, but you are also comfortable coaching less experienced team members in how to solve problems, or managing agencies to deliver where needed. You know that having a great model isn’t enough, you love to derive the “so what” from your models and tell compelling stories which inspire action and drive growth. A day in the life of... You’ll be responsible for using advanced analytics to provide robust measurements of marketing & trade investment across different business models, product categories and varied geographies. You will work closely with your stakeholders to provide guidance on how best to optimize and allocate marketing & trade investments in order to support the delivery of our commercial strategy. As part of this role you will need to : Share your experience & knowledge and build Nestlé’s internal modelling capability Partner with stakeholders to build and deliver a portfolio of advanced analytics initiatives Work closely with to identify and answer business problems/questions using appropriate modeling techniques on available data Evangelize and provide advisory services around data science capabilities and knowledge within Nestlé Work with large, complex data sets and solve non-standard problems What will make you successful Be educated to MSc level (or equivalent) in Math, Statistics, Physics, Operations Research, Econometrics or Data Science. Have proven experience of handling large datasets and reporting automation. Be able to demonstrate an excellent understanding of marketing mix modelling and price & promotion analytics. Experience with dynamic linear models/state space models is of particular interest. Have the ability to network and influence at senior levels both internally and externally. Be able to interpret data and explain business performance in an easy to understand way that tells a story to key stakeholders. Have proven experience of working in a matrix environment; achieving results through effective influencing and collaboration. Have advanced MS Excel, SQL, R, Python (or similar) experience Nestlé Nestlé enjoys a reputation as the world’s largest food and beverage company driven by our purpose - enhancing the quality of life of everyone, today and for generations to come. At Nestlé, we constantly explore and push the boundaries of what is possible with foods, beverages, and nutritional health solutions to enhance quality of life and contribute to a healthier future to better support individuals, families, communities and the planet. We have more than 2000 brands ranging from global icons to local favourites and are present in 190 countries worldwide. About IT in Nestlé We are a team of IT professionals from diverse cultures, genders and age groups in the world’s largest food and beverage company. We innovate every day through forward- looking technologies to create opportunities for Nestlé’s digital challenges with our consumers, customers, and employees. We have exciting positions in our new Nestlé global services operations based in Bangalore, which works alongside our Regional IT Hub in Sydney and Global IT hubs to provide technology services for Asia, Oceania, and Africa (AOA). This setup will design, implement, and maintain IT solutions and sharpen Nestlé’s focus in the growing areas of digital, analytics and innovation to support changing customer, consumer and shopper focus. When you join our IT team, you’ll have the opportunity to collaborate across local and global Nestlé teams and external partners to deliver innovative technologies that create tangible business value and contribute proactively to our sustainability goals. Our diversity brings fresh and innovative thinking to how we approach new and existing challenges while embracing different cultures, genders, sexual orientation, abilities and flexible ways of working.

Company Description Intelisync is a leading blockchain development and Web3 marketing firm, specializing in building secure and scalable decentralized applications and ecosystems. Our expertise includes Real-World Asset (RWA) tokenization, DeFi solutions, Layer 2 scaling, and AI integration. We are dedicated to advanced security and decentralized identity solutions, ensuring our platforms are resilient and future-proof. We also excel in Web3 marketing strategies to drive user growth and engagement and specialize in token creation, custom blockchain development, and advanced AI-driven solutions. Role Description This is a full-time on-site role for a Data Scientist located in Pune. The Data Scientist will be responsible for analyzing and interpreting complex data sets, developing and implementing data models, and working closely with cross-functional teams to provide actionable insights. The role involves day-to-day tasks such as performing statistical analysis, creating data visualizations, and contributing to data-driven decision-making processes. Qualifications Strong skills in Data Science, Data Analytics, and Data Analysis Proficiency in Statistics and Statistical Analysis Experience with Data Visualization tools and techniques Excellent problem-solving and analytical thinking skills Proficiency in programming languages such as Python or R Ability to communicate complex data findings effectively Bachelor's or Master’s degree in Data Science, Statistics, Computer Science, or related field Experience in blockchain or Web3 projects is a plus

Data Scientist/ML Scientist About Auxia Auxia is an AI-powered Growth and Personalization Platform that is reinventing how companies activate, engage, retain and monetize their customers. Auxia’s software delivers real-time personalization using ML that treats each customer as a unique individual, effectively creating a “cohort-of-one”. With Auxia, hundreds of personalized campaigns can be generated and deployed in minutes, doing away with static and tedious, rules-based segmentation and targeting. Auxia is easy to use, integrates with most major data and customer engagement tools, and frees up valuable internal resources. Our team started Auxia based on our collective expertise in advancing product growth at companies like Google, Meta, and Lyft. We saw a paradigm shift unfolding where the most successful teams drove significant revenue improvements and cost reductions by shifting from static, rules-based segmentation and targeting to real-time decision-making driven by machine learning. About the role As the core member of the Auxia Data Science team, you will play a significant role in driving the data science vision/roadmap and also in building and improving our Machine Learning models and Agentic AI products. You will perform research at the intersection of recommender systems, causal inference, transformers, foundational models (LLMs), content understanding and reinforcement learning and develop production grade models serving decisions to 10s of millions of users per day. You will work at the intersection of artificial intelligence, process automation, and workflow optimization to create intelligent agents that can understand objectives, make decisions, and adapt to changing requirements in real-time. You will also be responsible for performing in-depth analysis of customer data and derive insights to better understand customer problems and collaborate cross functionally across engineering, product and business teams. Responsibilities Design, implement, and research machine learning algorithms to solve growth and personalization problems and continuously fine-tune and improve them Design and develop AI-driven autonomous agents to execute complex workflows across various applications and objectives Implement and improve offline model evaluation methods Analyze large business datasets to extract knowledge and communicate insights to critical business questions by leveraging traditional statistical or machine learning methodologies Present and communicate data-based insights and recommendations to product, growth and data science teams at Auxia’s customers Stay updated on ML research through literature reviews, conferences, and networking Qualifications Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field. 7+ years experience in training and improving and deploying ML models, developing production software systems such as data pipelines or dashboards preferably at fast-growing technology companies Proficiency in ML frameworks (TensorFlow/PyTorch/Jax) and the Python data science ecosystem (Numpy, SciPy, Pandas, etc.) Experience with LLM, RAG, information retrieval etc in building production grade solutions Experience in recommender systems, feed ranking and optimization Experience in causal inference techniques and experimental design Experience working with Cloud services consuming and managing large scale data sets Thrives in ambiguity, ownership mindset, and willing to ‘get your hands dirty’ outside of the scope of your role (e.g. Product vision, strategic roadmap, engineering etc)