Top Data Scientist Jobs in Delhi

The Data Scientist will analyze and model data for ML systems, focusing on Personalization and Recommendation Engines, and collaborate with teams to enhance data-driven solutions.

The Data Scientist will analyze data, optimize ML systems for pricing, propose ML opportunities, collaborate with teams, and support data-driven decisions.

Build, deploy, and maintain ML and optimization models for a quick-commerce marketplace (matching, pricing, recommendations, ETA). Design experiments and causal analyses, engineer features from messy geospatial and conversational data, own production ML pipelines, monitor model health, and collaborate cross-functionally to deliver reliable, incremental improvements.

As a Data Scientist, assess business opportunities and promote data science use, developing and operationalizing analytics solutions with internal and external partners.

Design, train, validate, deploy and monitor ML models (pricing, dispatch, fraud, personalization). Perform EDA, feature engineering, statistical analysis, production-quality Python/SQL development, collaborate with product and engineering, and drive data quality, documentation, and knowledge sharing across the Data & AI domain.

Lead end-to-end development and deployment of machine learning, deep learning, NLP, and generative AI solutions. Apply architectures such as CNNs, RNNs, and Transformers; build NLP and RAG applications; optimize model scalability, latency, accuracy, and explainability; collaborate with stakeholders; and mentor junior data scientists while guiding technical delivery.

Lead customer-facing development and deployment of production-ready ML, Generative AI, and agentic AI solutions for supply chain challenges. Partner with customers from discovery through adoption, build scalable ML pipelines and prototypes, evaluate emerging AI technologies, collaborate cross-functionally, and mentor team members to drive measurable business impact.

Lead design, build, and deployment of scalable machine learning models using Python, SQL, and ML/DL frameworks. Process and train models on large datasets with Spark/Databricks/Hadoop, automate pipelines with Airflow and AWS EMR, and integrate models into AWS cloud applications. Drive end-to-end experiments, optimize pipelines and queries, and deliver production-grade, high-impact data science solutions.

Senior technical leader defining evaluation-driven development, modeling strategy, MLOps and platform direction on AWS. Oversees multiple agile release cycles, ensures measurable business impact, mentors data scientists, sets governance for evaluation, synthetic data, validation, cost and compliance across the ML portfolio.

Senior technical leader defining evaluation-driven development, modeling strategy, and MLOps for an AI/ML portfolio. Owns delivery across 45-day agile cycles, sets platform architecture and cost strategy on AWS, ensures governance/compliance, mentors senior teams, and demonstrates measurable business impact through rigorous evaluation and validation approaches.

Build data infrastructure and reliable pipelines, analyze product usage, train traditional and LLM-based models, define product metrics, run experiments, and translate findings into product and go-to-market decisions. The role combines data science, data engineering, product analytics, machine learning, and stakeholder communication, with ownership across data modeling, evaluation, experimentation, and product insight generation.

Design, prototype, and deliver agentic AI solutions using ML and generative models. Partner with product, engineering, and delivery teams to build, evaluate, and deploy LLM-based solutions, run experiments and POCs, and communicate technical recommendations to stakeholders.

The Senior Data Scientist will engineer Zoom's Revenue Intelligence Engine, developing scalable systems for lead scoring and churn prediction while collaborating with various teams to provide data-driven insights.

The Senior Data Scientist will lead ML initiatives, develop production-grade data science solutions, mentor junior team members, and collaborate with stakeholders to address complex problems.

Lead advanced analytics and ML projects: perform EDA, feature engineering, statistical modeling, and build/optimize production ML and Generative AI solutions (LLMs, embeddings, RAG). Collaborate with engineering and MLOps to deploy and monitor models, create visualizations and dashboards, translate insights for stakeholders, and mentor junior team members.

As a Senior Data Scientist, you will utilize analytical methods and programming skills to derive insights from data, design solutions, and communicate effectively with stakeholders.

Build and operate production ML models for entity resolution, deduplication, and telemetry pattern recognition. Deploy, monitor, and maintain models in streaming pipelines, work with graph databases, reason about networking telemetry, and collaborate with security and observability teams to improve detection, alert quality, and model reliability.

Lead cross-functional ML initiatives: choose modeling approaches, define business-linked evaluation metrics, validate with synthetic and real data, deliver MLOps-enabled models on AWS, ensure reproducibility, compliance, cost optimization, and incremental value within short agile release cycles.

Lead cross-functional delivery of ML and analytics solutions: select modeling approaches, define business-aligned evaluation metrics, validate with synthetic and historical data, implement MLOps on AWS, ensure reproducibility, cost optimization, and regulatory explainability, and ship incremental value in short agile release cycles.

The Senior Data Scientist will design and implement data pipelines, develop models for player engagement, and collaborate with teams to deliver insights and solutions.

The Senior Data Scientist & Engineer will build and manage data infrastructure, analyze product usage, build models, track metrics, run experiments, and communicate insights to guide product decisions.