Job Highlights:
- 11-13 years in analytics/AI with expertise in Python, SQL, PyTorch/TensorFlow, and statistical modelling.
- Lead end-to-end data science projects including model development, validation, and production support.
Roles and Responsibilities:
- Own data science initiatives end-to-end, including problem framing, exploratory analysis, model development, validation, and production support.
- Apply statistical and classical machine learning methods (e.g., regression, classification, tree-based models, ensembles, time-series) to solve business problems.
- Design, develop, and evaluate predictive and analytical models using rigorous statistical and ML techniques.
- Perform feature engineering, model selection, tuning, and performance evaluation; clearly document assumptions and tradeoffs.
- Build advanced machine learning and deep learning models using PyTorch and/or TensorFlow, and support production-quality implementation.
Skills Required:
- 11-13 years of experience in analytics, AI/digital product development, or data-driven platform roles.
- Data science and end-to-end ML lifecycle ownership (development, validation, deployment, monitoring).
- Advanced proficiency in Python and SQL for analytics and model development.
- Hands-on machine learning and deep learning using scikit-learn, PyTorch, and/or TensorFlow.
- Strong statistical modelling and ability to translate ambiguous business problems into structured analytical approaches.
Good to Have:
- Agentic AI experience and familiarity with AI experimentation for iterative product development.
Education: B.Tech (any branch); Bachelor's or master's degree in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative field (PhD preferred).
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