Senior Assistant Vice President leading machine learning model development for banking. Collaborating with cross-functional teams to drive innovative solutions and business benefits.
Responsibilities
Lead the development and deployment of machine learning models
Collaborate with cross-functional teams and provide technical leadership
Guide junior data scientists on best practices in model development and MLOps
Develop robust models to solve business problems and drive benefits
Support and review junior data scientists’ submissions
Manage queries raised by model validation teams and defend models
Continuously evaluate new tools, technologies, and frameworks relevant to ML in finance
Requirements
8+ years in Retail banking
Strong business knowledge of banking analytics across the retail banking customer lifecycle
Master’s or Similar in Computer Science, Data Science, Statistics, Applied Mathematics, or a related quantitative field
End-to-end hands-on ML solution development experience
Strong experience with model development, deployment and monitoring in production environments
Expert in Python, SQL, ML libraries (Numpy, Pandas, Scikit-learn, TensorFlow, PyTorch) and techniques (Regression, Decision Trees, Ensembles: XGBoost, GBM, Random Forest, Unsupervised Learning, etc.)
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