Risk Strategy and Analytics - Credit & Fraud

Description:

• The ideal candidate will have strong technical skills combined with the ability to distill down complex financial concepts to simple narratives.
• You will have an in-depth understanding of Credit & Fraud Risk, ideally in the payments industry.
• You are adept at building and deploying risk policies, models and metrics.
• You will work heavily partnering cross-functionally to drive core risk initiatives including risk appetite, emerging risk identification, portfolio health, and risk-based pricing.
• Drive risk initiatives including risk appetite, emerging risk identification, portfolio health, and risk-based pricing
• Analyze large portfolios of merchants, using data analytics to assess the performance of different portfolio segments and to diagnose deviations from targets
• Lead the design and roll-out of Risk Strategies across Credit & Fraud to achieve the desired balance between risk and reward
• Roll out portfolio monitoring and reporting tools to facilitate ongoing review of key risk metrics
• Evaluate emerging risks, analyze key risk trends and lead the development of prudent risk management in enabling business growth initiatives
• Nurture deep, trusted partnerships with sales teams across Stripe to facilitate risk-aware decision-making
• Partner closely with data science and product teams to expand toolkit of risk mitigations

Requirements:

• 6+ years of relevant experience in Credit or Fraud Risk within the Small Business or Consumer space.
• Experience at high-growth technology and/or financial services companies. Investment banking, management consulting and/or private equity experience will also be considered
• Strong data analytics skills and hands-on experience working with very large amounts of data.
• Extensive experience using SQL and ideally experience using other data manipulation languages and libraries (e.g. Python, R).
• Experience designing and building Risk strategies end-to-end, from initial design to implementation. You are comfortable interpreting Risk and Reward metrics, performing what-if analyses and turning analytical insights and business goals into actionable strategies.
• Demonstrated ability to build collaborative working relationships with other teams, particularly data science, engineering, sales, and product.
• Experience working with and synthesizing large data sets independently. Demonstrated ability to abstract signals from noise and build canonical data sets.
• Strong presentation skills and ability to transform data into a dynamic narrative. You have deep empathy for users of credit risk information and are able to create succinct narratives out of quantitative analyses.
• Excellent verbal and written communication skills.

Benefits: