Credit Risk Manager

Job Description

REQUIREMENTS

• Bachelor/Master’s degree with a quantitative background (e.g., Statistics, Math, Economics, Computer Science, Engineering, or Business).
• 5+ years in credit risk management or data science within consumer lending.
• Comfortable working in a fast-moving, evolving environment where priorities shift, and initiatives move quickly.
• Self-driven, with intense focus on results. High curiosity with a proven track record of probing root causes, challenging the status quo, and designing out-of-the-box solutions.
• Strong analytical and problem-solving skills, combined with solid business judgment
• Clear, strong communicator who can translate complex data into simple, actionable insights for any audience.
• Strong team player and comfortable interacting with partners across multiple teams and at varying levels of seniority
• Advanced proficiency in SQL and Python/R for pulling, cleaning, and modeling complex relational data independently.
• Practical application of predictive modeling, customer segmentation, and statistical procedures to evaluate risk and borrower behavior.
• Experience with Tableau, Power BI, and Looker.
• Adhere to all company security policies and data handling procedures.
• Complete mandatory security awareness training within required timeframes.
• Promptly report any suspected security incidents or suspicious activity to the Security team.

RESPONSIBILITES

• Continuously refine and modernize credit underwriting strategies using advanced analytics to optimize risk decisions across lending products.
• Analyze historical loan performance data to model credit expansion initiatives, identify new customer segments, and optimize funnel conversion.
• Perform root-cause analyses on credit losses and default trends, partnering with Fraud Risk Management to sharpen fraud controls.
• Develop valuation models to estimate segment-level economics and advise Capital Markets on yield projections and performance assumptions.
• Partner with Product, Engineering, and Data Science to design A/B tests that balance risk control, conversion lift, and user experience.
• Track and validate pre- and post-implementation performance for all deployed credit and fraud rule changes.
• Design monitoring frameworks to track new product launches at a granular segment level, identify emerging portfolio risks, and inform executive decision-making.
• Present our client’s underwriting methodology to investors and serve as a core contact for due diligence and portfolio performance inquiries.
• Collaborate with Legal and Compliance to ensure all credit strategies strictly meet regulatory requirements.
• Conduct ad hoc quantitative analyses to support broader Credit, Operations, and Product objectives.

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