Financial Data Scientist, Capital Management

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Job description

We're working on making the global financial system programmable. This is one of the largest opportunities for impact in the history of computing, on par with the rise of modern operating systems. Enabling the realization of this opportunity and simultaneously ensuring we optimize the deployment of capital and maximize our profitability, the Capital Management team plays a critical role in the company's financial health.

We're looking for an experienced Data Scientist to partner with the Capital Management team to drive the use of data and modeling to deploy capital in the highest valued use cases. You will help us to build integrated capital planning and capital attribution systems with proprietary data models, develop capital efficiency metrics and conduct analyses to inform our financial resource needs and business decisions. In doing so, you will work cross-functionally to measure our risks and shape our understanding of how Stripe is performing as a business, as well as what our best opportunities are for continued growth.

The ideal candidate has experience in capital planning/attribution frameworks and systems, machine learning and statistical modeling, thinks creatively about measurement that leads to actionable outcomes, and values rigor in data and modeling.

You Will

• Develop and maintain capital planning, capital attribution and capital reporting systems
• Conduct trend and sensitivity analyses on risk factors, profitability and capital requirements, and develop data-driven recommendations to inform business decisions
• Develop statistical and machine learning models to identify patterns in large scale data related to user activity, product usage, profitability and risks, and formulate recommendations for driving business strategy
• Develop user, regional, legal entity and product level capital efficiency metrics
• Spin up proofs of concept for different applications and iterate to build scalable solutions
• Develop Key Risk Indicators (KRI's) related to our capital management processes including overall equity and liquidity adequacy ratios and capital efficiency metrics
• Ensure that our capital management systems are appropriate for the scale and complexity of our business
• Design fully automated systems that capture risk-adjusted returns and capital attribution across millions of users in 120+ countries
• Work with Product and Sales to analyze new business opportunities, share insights, assess risk-reward profiles and inform our strategy and pricing
• Collaborate with cross-functional teams, particularly Finance, Risk, Product, Sales and Engineering, and inform how we manage our capital base
• Build scalable automation solutions utilizing SQL, Spark, and visualization tools
• Shape and influence our data models and instrumentation to generate insights and develop new data products and models
  

Our Ideal Candidate Will Have

• 5+ years of data science/quantitative modeling experience, including 3+ years experience analyzing large data sets in the financial sector
• A PhD or MS in a quantitative field (e.g., Quantitative Finance, Economics, Mathematics, Sciences, Engineering, Statistics)
• Strong working knowledge of SQL, R, Python, Matlab, C++, or equivalent.
• Solid business acumen and experience in synthesizing complex analyses into interpretable content
• Strong understanding of financial industry models and capital planning/attribution frameworks and system architecture
• Expertise in statistics and experimental design
• A demonstrated ability to manage and deliver on multiple projects with a high attention to detail
• Ability to communicate results clearly and a focus on driving impact
• A builder's mindset with a willingness to question assumptions and conventional wisdom