Assistant Vice President – Data Science

Translate business problems into data science projects by defining clear hypotheses, success metrics, and validation methods.

Explore, clean, and transform structured and unstructured data using Python and SQL to prepare high-quality datasets for modeling.

Design, train, and evaluate machine learning models using appropriate algorithms and statistical techniques (e.g., regression, classification, clustering, NLP, forecasting).

Collaborate with engineering and platform teams to productionize AI models through reproducible pipelines and CI/CD workflows.

Apply model explainability, fairness, and interpretability techniques (e.g., SHAP, LIME, feature importance) to ensure transparency and accountability.

Support AI governance activities, including Model Risk Management (MRM) processes, ensuring compliance and responsible use of AI.

Conduct and analyze A/B tests or controlled experiments to assess model and feature performance.