Senior Data Scientist

Job Description

We are seeking a Senior Data Scientist with strong hands-on experience across Traditional AI/ML and Generative AI (GenAI). This role will primarily focus on one project at a time, owning core experimentation and implementation workstreams, while also guiding and grooming junior data scientists to ensure consistent, high-quality delivery. You’ll work closely with the Lead Data Scientist, AI Engineers, Data Engineers, and MLOps to build scalable, production-ready AI capabilities and support client-facing discussions and demos as needed.

Job Responsibility

Execute end-to-end AI/ML experimentation for a single project: problem framing, dataset readiness, feature engineering, model training/tuning, evaluation, and iteration
Build and optimize GenAI pipelines using proprietary and open-source models depending on project needs
Contribute to LLM-driven feature development with working knowledge of model behavior, embeddings, prompting strategies, context management, and evaluation
Implement and improve RAG pipelines (document ingestion, chunking strategies, embeddings, retrieval, reranking, grounding, and evaluation)
Develop agentic workflows using modern agent frameworks and tool integrations (multi-step execution, tool use, safety/guardrails)
Assist in defining evaluation methods for GenAI (faithfulness, relevance, hallucination risk, latency, cost)
Work with engineering and MLOps teams to transition experiments into production-grade pipelines
Contribute to performance tuning, observability, and reliability of AI services (metrics, logging, monitoring, error analysis)
Ensure implementation follows best practices for maintainability, scalability, and cost efficiency
Guide and groom junior data scientists through structured mentorship: task planning, implementation reviews, and feedback
Help define reusable assets (notebooks, evaluation templates, baselines, documentation) to improve team velocity and quality
Support the Lead Data Scientist in breaking down tasks and estimating effort for your workstream
Participate in technical discussions with internal stakeholders and clients
support demos and walkthroughs where applicable
Clearly communicate experimental results, trade-offs, and recommendations through structured documentation and presentations

Requirements

5+ years of hands-on experience in data science / machine learning with delivered outcomes
Practical experience in both Traditional ML (supervised/unsupervised methods, NLP, time series, recommendations, etc.) and GenAI (LLM-based features)
Hands-on experience building or contributing to RAG systems
familiarity with agentic frameworks is strongly preferred
Solid understanding of model evaluation, experimentation rigor, and iterative improvement cycles
Ability to independently own tasks within a project and deliver with minimal supervision
Experience mentoring or guiding junior team members through reviews and coaching
Strong communication and documentation skills

Nice to have

Graduates from Tier 1 / Tier 2 colleges preferred (e.g., IITs, NITs, IIITs, BITS, top state universities and reputed private institutions)
Experience with enterprise-grade requirements: data privacy, security, governance, and compliance
Familiarity with open-source and proprietary model ecosystems and selection trade-offs
Exposure to MLOps/LLMOps practices (CI/CD, model/prompt versioning, monitoring, A/B testing)

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Senior Data Scientist – GenAI & Traditional AI

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