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Mid-level ML role, metro location, popular title and broad skillset increase applicant competition.
Requires financial-services domain experience and ML expertise, limiting easy transfer across industries.
Explicit 5-8 years, financial-services experience, team leadership and mandatory ML skillset make filters strict.
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Lead development and implementation of machine learning models targeting personalization, cross-sell, acquisition, retention, and risk modeling.
Manage and mentor a team of data scientists and analysts while ensuring high data quality and accuracy for modeling.
Collaborate with cross-functional teams to deliver data-driven solutions and maintain up-to-date industry knowledge in ML and data analysis.
Bachelor's or Master's degree in Mathematics, Statistics, Engineering, or related quantitative discipline.
5-8 years of experience in data or business analysis within financial services.
Proficiency in SQL and Python/PySpark with experience handling large and complex datasets.
Experience building and managing teams of data scientists and analysts.
Experienced in financial services data science with strong operational ownership of data quality and campaign execution.
Capable of working with external data providers and internal IT teams to establish data pipelines and governance.
Demonstrates ability to translate complex data into actionable dashboards tracking key business KPIs.