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 mitigationsRequirements: 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:

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