Data Scientist, Risk Interventions

Remote in the United States

Applications have closed

Stripe

Stripe powers online and in-person payment processing and financial solutions for businesses of all sizes. Accept payments, send payouts, and automate financial processes with a suite of APIs and no-code tools.

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Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

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

  • Build statistical and machine learning models to measure all aspects of the onboarding and compliance processes
  • Create metrics and dashboards for key performance indicators and deep dive investigations to understand and optimize the drivers of those indicators
  • Design, analyze, and interpret the results of experiments. Drive the collection of new data and the refinement of existing data sources
  • Partner closely with product, engineering, and strategy teams to shape the team’s strategy and prioritize the most important projects to achieve its goals
  • Effectively communicate the outcomes of your work to key stakeholders

Who you are

You’re an experienced data scientist with experience partnering closely with engineering and business teams to ensure practical, data informed strategy.  You are excited and curious about understanding dynamics of complex systems in the business and strive to continuously learn new skills.  You are motivated to develop practical solutions to business problems always focusing on balancing technical rigor with business context aiming for optimal solutions.

Minimum requirements

  • 5+ years data science/quantitative modeling experience
  • A PhD or MS in a quantitative field (e.g., Operations Research, Economics, Statistics, Sciences, Engineering)
  • Strong working knowledge in a scientific computing language (Python, R, etc.) and SQL
  • Strong knowledge and hands-on experience with data science, machine learning, statistics, and experimentation for commercial applications
  • Experience building scalable quantitative calculations in modern technical stacks
  • A demonstrated ability to manage and deliver on multiple projects with a high attention to detail
  • Strong stakeholder management skills with a demonstrated ability to shape prioritization efforts  across multiple stakeholder teams
  • The ability to communicate results clearly with a focus on driving impact

Preferred qualifications

    • Experience building ETL solutions utilizing Presto, Spark, Airflow or similar tools
    • Experience with causal inference methods
    • Experience partnering with globally distributed teams

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Airflow Causal inference Economics Engineering ETL Machine Learning ML models PhD Python R Research Spark SQL Statistics

Regions: Remote/Anywhere North America
Country: United States
Job stats:  21  10  0
Category: Data Science Jobs

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