- Develop statistical and machine learning models for QbD, CPV, PAT, and process monitoring use cases, including CQA modeling, anomaly detection, and multivariate process analysis.
- Advise product managers and product leaders on how advanced analytics and modeling can create value in the product suite.
- Collaborate cross-functionally with engineering and domain experts to ensure models are technically sound, explainable, and production-ready.
- Create prototypes and proofs-of-concept for recent analytics-based product features.
- Ensure modeling practices comply with regulated environments (GxP, GMP).
- Document modeling approaches, assumptions, limitations, and usage patterns clearly for internal and external stakeholders.
- Contribute to product discovery by identifying opportunities where AI, ML, or statistical methods can improve usability, decision-making, or automation.
📌 Sr. Data Scientist (Chennai)
🏢 ValGenesis
📍 Chennai
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