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Tier-1 brand, metro location, and broad ML skillset increase applicant density.
Financial services model governance and domain-specific constraints make skills less transferable.
Requires VP-level ML expertise, Python, SageMaker, governance, and leadership—strong mandatory filters.
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Lead the design and implementation of data science tools and models to drive customer and business solutions.
Collaborate with business stakeholders to define problems, develop hypotheses, and deliver advanced analytics and machine learning solutions ensuring ethical standards and model governance.
Manage and guide multi-disciplinary data science teams in agile settings to achieve project outcomes, while handling stakeholder engagement and promoting best practices in data usage and model development.
Academic background in STEM discipline such as Mathematics, Physics, Engineering, or Computer Science.
Proven proficiency in Python and libraries like Pandas, NumPy, and Scikit-learn.
Experience with cloud platforms such as AWS Sagemaker and hands-on knowledge of statistical modelling, machine learning, and data visualisation tools.
Work Experience Required: Not explicitly mentioned in the JD.
Demonstrates ability to lead and coordinate agile, multi-disciplinary data science teams towards project delivery.
Strong technical expertise spanning data science, machine learning including LLMs, software engineering, and cloud applications.
Experienced in translating complex business needs into advanced analytical solutions within a structured governance and ethical framework.