Data Science Manager, Risk Interventions

Key Skills

Analytical and Problem solving, Data science techniques, ETL frameworks, Large data sets, Machine learning techniques, Presto, Python Programming, R Programming, SPARK Programming, SQL

Job Description

About the team

The Risk Interventions Data Science Team aims to ensure we achieve the right balance between mitigating risk and enabling our customers to achieve their business objectives. Working cross-functionally with various teams within the organization, the team is focused on developing models, methods, and frameworks for ensuring efficient compliance with regulatory requirements, appropriately targeted interventions and a low friction user experience.

What you’ll do

As the Risk Interventions Data Science Manager will lead a team of data analysts and scientists that work closely with partners all across the Risk space. You will help your team to build, own and maintain important pipelines, ML models and analytics tools that help power our risk decision and intervention processes and shape the strategy of the entire Risk organization through data-driven insights. To accomplish this, you will ensure that each member of the team is strongly focused on delivering practical solutions to business problems and clear communication of the impact these solutions have towards Stripe's goals.

Responsibilities

• Set the vision and guide the data science team to help Stripe develop world class user experiences while protecting Stripe, our partners, and merchants against fraud and other risks 
• Measure the impact of Risk Interventions on both authentic merchants and fraudulent actors
• Working with engineering, product, strategy and operational leaders to integrate meaningful quantitative results with business execution and risk reductions
• Effectively communicate the outcomes of your analysis to key stakeholders, including senior management
• Mentor and develop the careers and capabilities of junior data scientists

Who you are

You’re an experienced manager and quantitative engineer, e.g. financial engineer, data scientist or machine learning engineer with significant experience developing and deploying, mathematical models to generate significant value. You have an interest in leveraging data science and any other quantitative methods required to optimize the commercial effectiveness of a complicated, data driven organization. You are energetic, risk taking, personally accountable and driven to impact business outcomes.

Minimum requirements

• 5+ years experience, including 2+ years managing a team of data scientists, machine learning or financial engineers.
• A PhD or MS in a quantitative field (e.g., Operations Research, Economics, Statistics, Sciences, Engineering)
• Experience in a scientific computing language, e.g. Python and SQL
• Strong knowledge and hands-on experience with data science, machine learning, statistics, financial calculations and experimentation for commercial applications
• Experience in working with multiple cross-functional teams to deliver results
• The ability to communicate results clearly

Preferred qualifications

•  Experience in building scalable ETL solutions utilizing SQL, Presto, Spark or other similar tools
• Experience in combating fraud or other aspects of financial risk

Pay and benefits

The annual US base salary range for this role is $233,398 - $329,503. For sales roles, the range provided is the role’s On Target Earnings (OTE) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. This salary range may be inclusive of several career levels at Stripe and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, and location. Applicants interested in this role and who are not located in the US may request the annual salary range for their location during the interview process.