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Metro location, popular data science role, and broad skill requirements increase candidate competition.
Senior bank-specific model governance and stakeholder requirements make industry experience highly important.
Role requires specific ML, cloud, governance, and leadership skills, making filters strict.
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Lead the design and implementation of data science tools and machine learning models to drive customer solutions at a Group level.
Collaborate with business stakeholders to define analytics problems, develop hypotheses, and deliver data-driven, ethically sound solutions using advanced visualization and modeling.
Manage and lead agile, multi-disciplinary data and analytics teams, ensuring governance, model validation, risk mitigation, and scalability of solutions.
Academic background in STEM discipline (Mathematics, Physics, Engineering, or Computer Science).
Proven proficiency in Python and libraries such as Pandas, NumPy, Scikit-learn.
Experience with cloud platforms, specifically AWS Sagemaker.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in statistical modeling, machine learning techniques including LLMs, and advanced data visualization in a business context.
Skilled at engaging and managing multiple stakeholders while leading cross-functional teams in an agile environment.
Demonstrates expertise in model governance, ethics, validation, and scaling of data science solutions.