The Data Scientist supports the Responsible AI program by embedding with AI Factory teams to ensure GenAI applications are safe, transparent, and measurable. Key duties include executing evaluations for hallucination and fairness, developing benchmark datasets, and prototyping emerging RAI techniques.
Remote Data Scientist Jobs in India (45)
Search = Data Scientist
Remote in = India
Design, build, and deploy production-ready machine learning solutions to solve real business problems for enterprise clients. This includes the full lifecycle from data exploration and feature engineering to model deployment and continuous iteration.
Architect and implement optimization solutions using MILP solvers and deploy FastAPI-based microservices for ML workflows. Lead and mentor a team of engineers while serving as the primary technical point of contact for clients.
Design and deploy multi-agent systems and generative AI applications to enable autonomous decision-making and optimize business processes. Implement RAG workflows, agent-to-agent communication protocols, and scalable AI architectural solutions using cloud infrastructure.
Extract and analyze large datasets from telemetry and test sources to derive actionable insights for agricultural machinery. Develop and refine machine learning models to optimize product performance and predict maintenance needs.
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The Data Scientist will design, build, and deploy production-ready machine learning solutions for enterprise clients. This involves managing the full lifecycle from data exploration and feature engineering to model deployment and continuous iteration.
The Data Scientist will collaborate closely with a senior research team member on cutting-edge Applied AI, infrastructure, and tooling to democratize Generative AI. Example projects include building RAG pipelines, creating Python libraries for GenAI on AWS, and implementing new neural network architectures.
As a Data Scientist, you will build production-grade ML systems that drive real-world outcomes such as energy efficiency and predictive maintenance. You will collaborate with engineers and product managers to translate raw sensor data into reliable models.
The Data Scientist will deliver data analytics projects and implement high-impact strategies for Visa clients in the Asia Pacific region. Key duties include driving credit card portfolio strategies and acting as an analytics advocate to unlock business value.
Research and develop advanced statistical and machine learning models for large-scale, high-dimensional energy data. Productize these models into production-quality code and collaborate with cross-functional teams to solve business challenges.
The role involves owning end-to-end data science projects across Credit Risk, Growth, and AI initiatives to drive business decisions. You will develop models for underwriting, fraud, and personalization while evaluating new modeling approaches and alternative data sources.
The role involves designing and implementing end-to-end ML and Deep Learning pipelines for regression and industrial control use cases. Responsibilities include optimizing neural network architectures and collaborating with cross-functional teams to integrate solutions into production.
Design and implement end-to-end machine learning systems from research to production to optimize customer engagement workflows. Collaborate with product managers and engineers to define the vision and strategy for AI-driven products.
Design and implement end-to-end machine learning systems from research to production. Collaborate with product managers and engineers to optimize customer engagement workflows through data-driven metrics and tools.
Develop next-generation weather forecasting systems for India by running regional NWP models and creating large-scale ML-ready datasets. You will integrate physics-based modeling with machine learning to improve nowcasting and extreme event prediction for the renewable energy sector.
Develop and operate cycling data assimilation pipelines to improve weather forecasting models for the renewable energy sector. Create large-scale, ML-ready weather datasets and integrate physics-based modeling with machine learning systems.
Develop machine learning models and data products for risk, fraud, and collections management to enhance financial inclusion. Lead end-to-end data pipelines and collaborate with compliance and risk management teams for model governance.
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Senior Data Scientist, Ecosystems
Wikimedia Foundation
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Full Time
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3 Weeks Ago
Wikimedia Foundation
The role involves integrating fragmented internal and external data to create a unified view of user discovery and content usage. You will develop automated systems to detect content gaps and establish metrics to track content utilization within LLMs and generative search engines.
Engineer Zoom's Revenue Intelligence Engine to transform telemetry data into actionable insights for customer growth and retention. This includes building scalable ML systems for lead scoring and churn prediction while collaborating with Product and Data Engineering teams.
Develops scalable algorithms, models, and tools to extract insights from large, diverse data sets for product and operational improvements. Collaborates with internal and external teams to analyze data quality, investigate fraud, and communicate findings through reports and visualizations.
You will build and own data infrastructure, pipelines, and warehousing while analyzing product usage to drive product decisions. Additionally, you will develop machine learning models and LLM-based systems to provide actionable insights that influence product strategy.
You will drive the definition and development of new products and methods, focusing on innovation in data processing and automation of statistical procedures. The role involves prototyping solutions, collaborating with cross-functional teams, and engaging with stakeholders to deliver high-quality, scalable data applications.
Data Scientist - Research & Analytics
Pratham International
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Full Time
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7 Weeks Ago
Pratham International
The Data Scientist will manage project-level data operations and perform rigorous analyses to inform program design and decision-making. They will also design predictive models and translate technical findings into actionable insights for diverse stakeholders.
The role involves creating and curating high-quality datasets for AI/LLM training and generating synthetic data and prompts. Additionally, the specialist will evaluate AI-generated outputs for quality and accuracy while reviewing code and data visualizations.
002ACH -Data Scientist
Augusta Hitech Soft Solutions
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Full Time
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8 Weeks Ago
Augusta Hitech Soft Solutions
Design, develop, and deploy AI and machine learning models using advanced cloud frameworks and services. Collaborate with cross-functional teams to integrate scalable AI solutions into business applications.
The Senior Data Scientist will apply analytical methods to solve business problems and design end-to-end analytical solutions. They will also communicate results and recommendations clearly to stakeholders.
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Support the build of end-to-end Generative AI applications such as chatbots and Talk-to-Data systems. Implement RAG pipelines and perform model selection and fine-tuning for various models.
As a Sr Data Scientist, you will apply advanced analytics, machine learning, and AI techniques to solve complex business challenges. You will develop and deploy sophisticated data science solutions that drive operational efficiencies and enhance decision-making capabilities.
The role involves designing, optimizing, and maintaining scalable ETL pipelines using PySpark and Databricks on cloud platforms, alongside developing automated data validation processes for quality checks. Responsibilities also include building and tuning ML/AI and optimization models, engaging with business stakeholders, and collaborating with cross-functional teams.
The role involves designing, implementing, and maintaining robust data pipelines, processing data via APIs, and developing reporting layers like dashboards and automated reports. Key tasks include building predictive and optimization models for areas such as player lifetime value and churn prediction, and applying state-of-the-art AI/ML techniques.
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