Senior Quantitative Risk Analyst
The Senior Quantitative Risk Analyst position will report to Senior Risk Analytics Manager.
As the Senior Quantitative Risk Analyst, you will:
• Lead loss forecasting by leveraging data science models and applying business overlays to project portfolio performance.
• Monitor and analyze credit metrics across multiple loan products, identifying key risks, trends, and opportunities.
• Prepare and present portfolio forecasts and credit/fraud performance updates to executives, the Board, and rating agencies.
• Validate and challenge credit and fraud risk models to ensure methodological soundness, transparency, and regulatory compliance.
• Partner cross-functionally with Finance, Capital Markets, and Data Science to align risk insights with business strategy.
About You:
• 3+ years in a data-driven role, ideally within credit or fraud risk.
• Strong proficiency in SQL for data extraction and Python for statistical modeling and analysis.
• Experience with loss forecasting, particularly in consumer lending products.
• Skilled in data visualization and BI tools (e.g., Looker, Tableau) as well as Excel and PowerPoint.
• Strong analytical thinker with excellent communication and presentation abilities.
• Detail-oriented, intellectually curious, and able to manage multiple priorities under tight deadlines.
Even Better:
• Experience in student loans, personal loans, or credit cards.
• Familiarity with regulatory compliance in the lending industry.
• Prior exposure to risk model development or enhancement.
• Background in efficiency improvements and automation.
• Ability to independently research and implement innovative modeling approaches.
Where:
• This role will be based in the US.
#LI-KB1
Apply Now
Apply Now
As the Senior Quantitative Risk Analyst, you will:
• Lead loss forecasting by leveraging data science models and applying business overlays to project portfolio performance.
• Monitor and analyze credit metrics across multiple loan products, identifying key risks, trends, and opportunities.
• Prepare and present portfolio forecasts and credit/fraud performance updates to executives, the Board, and rating agencies.
• Validate and challenge credit and fraud risk models to ensure methodological soundness, transparency, and regulatory compliance.
• Partner cross-functionally with Finance, Capital Markets, and Data Science to align risk insights with business strategy.
About You:
• 3+ years in a data-driven role, ideally within credit or fraud risk.
• Strong proficiency in SQL for data extraction and Python for statistical modeling and analysis.
• Experience with loss forecasting, particularly in consumer lending products.
• Skilled in data visualization and BI tools (e.g., Looker, Tableau) as well as Excel and PowerPoint.
• Strong analytical thinker with excellent communication and presentation abilities.
• Detail-oriented, intellectually curious, and able to manage multiple priorities under tight deadlines.
Even Better:
• Experience in student loans, personal loans, or credit cards.
• Familiarity with regulatory compliance in the lending industry.
• Prior exposure to risk model development or enhancement.
• Background in efficiency improvements and automation.
• Ability to independently research and implement innovative modeling approaches.
Where:
• This role will be based in the US.
#LI-KB1
Apply Now
Apply Now