Data Science Sr Manager

As the Head of Customer Behavior Modeling, you will lead a team of data scientists to develop and implement data and machine learning solutions that drive the profitability and efficiency of the card customer management lifecycle. Your work will support key initiatives, including line management, customer balance build programs, and collections.

Experience:

• Bachelor’s degree and above, in Economics, Finances, Statistics, Mathematics, Physics, or other quantitative discipline;
• Expert in SQL with proficiency in Python or another scripting language, with the interest and initiative to learn relevant new technologies;
• Experience building predictive models, customer lifetime value models, or other financial models (DCFs);
• 4+ years of experience leading or collaborating with data scientists for business problem-solving or model development;
• 2+ years of working experience in the credit industry;
• 1+ years of working experience in designing and executing A/B tests;

Skills and attitudes:

• Proven ability to drive projects independently;
• Solid oral and written communication skills, particularly in conveying analytical concepts and methods;
• A collaborative team player who excels in effective communication, cross-functional collaboration, and aligning efforts for the company’s overall benefit;
• Exhibits a demonstrated capacity to perform under pressure, meet tight deadlines, and respond proactively, decisively, and flexibly to challenges;
• Possesses a deep passion for data, a keen interest in business operations, and an ever-ready attitude to confront problems head-on.

Bonus Points:

• Experience developing a solution for credit card valuations using a behavior model;
• Demonstrated experience collaborating with product managers and backend engineers for the execution and monitoring of tests or decision processes;
• A proven track record of rapidly acquiring proficiency in new technologies, concepts, and tools.

Job responsibilites:

• Lead and mentor: Guide a team of data scientists in analyzing complex datasets to extract meaningful customer insights.
• Collaborate: Work closely with business analysts to translate data-driven insights into actionable business strategies.
• Problem-solving: Convert business challenges into modeling opportunities, ensuring alignment with strategic goals.
• Model Development: Oversee the full lifecycle of production model development, from conception to implementation, in partnership with MLOps, Data Engineering, and Engineering teams.
• Model Maintenance: Ensure the continuous monitoring and optimization of credit models to maintain effectiveness.
• Strategic Testing: Design and execute tests to evaluate customer behavior patterns and validate business hypotheses.