Lead Data Scientist
Philips (company site, opens in a new tab)7+ yrsBengaluruOn-siteDirect career pageEst. 30–50 LPA
Posted 16h ago
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Job description
Structured overview of role & requirements
About This Role
- Own end-to-end development and deployment of production-grade ML and Generative AI systems, including model training, scalable cloud deployment, and ongoing performance monitoring.
- Develop and maintain ML pipelines, analytics products, dashboards, and oversee data quality, governance, and single source of truth for commercial datasets.
- Partner with senior business stakeholders to translate complex analytics into decision-ready insights and AI-enabled solutions that drive measurable outcomes.
Minimum Requirements
- 7-12+ years of hands-on Data Science / ML Engineering experience with multiple end-to-end production deployments.
- Strong programming skills in Python and SQL; proficiency with ML frameworks (PyTorch/TensorFlow) and GenAI technologies (RAG, MCP, fine-tuning, embeddings).
- Experience deploying and operating ML/LLM applications on AWS or Azure, including CI/CD, model registry, monitoring, and pipeline orchestration.
- Bachelor’s degree in engineering, Computer Science, Statistics, Economics, Mathematics, or related quantitative fields; Master’s preferred. Onsite office presence required (minimum 3 days/week).
Ideal Candidate Profile
- Proven track record of owning full analytics domains and production ML systems beyond isolated analyses.
- Demonstrated expertise in GenAI delivery with experience shipping LLM applications with quality controls and safety measures.
- Experienced in collaborating with senior stakeholders across business units to influence decision-making through insight-driven communication in complex, matrixed environments.