• Locations
    • United States
    • San Francisco
  • Date Posted
  • May. 26, 2021
  • Function
  • Business Intelligence
  • Sector
  • Financial Services

Build the world’s fastest Identity and Checkout products

Company Mission

Our mission is to make buying online faster, safer and easier for everyone. Fast Login and Fast Checkout enable a one-click sign-in and purchasing experience that makes it easier for people to buy and merchants to sell. The company’s products work on any browser, device or platform to deliver a consistent, stress-free purchasing experience. Fast is entirely consumer-focused and invests heavily in its users’ privacy and data security. Headquartered in San Francisco but open to globally remote, we are a founders-led, privately held company funded by Stripe, Index Ventures, Susa Ventures and other world-class investors.

We are committed to diversity and inclusion, and demonstrate our values through equitable pay, fantastic benefits, and access to all reasonable accommodations.

The Payments & Risk team at Fast strives daily to build and operate a world-class payment processing platform free of payment failures, void of fraud, and as reliable as clockwork for both buyers and sellers engaged in e-commerce across the Internet. Our team is searching for an experienced Risk Data Analyst to help us achieve our mission. This will be a high-impact role ensuring our buyers and sellers maintain trust in our Checkout solution. If you’re passionate about payments, enjoy leveraging large datasets to make data-driven decisions, and want to stop fraudsters in their tracks, then this role is for you! Come join us as we upgrade the internet by creating a new, frictionless online checkout experience.


  • Leverage data to test and deploy targeted rules designed to prevent known and emerging fraud trends across many product lines for both buyers and sellers on Fast’s platform
  • Evaluate the performance and accuracy of Data Science (DS) models, and work with the DS team to debug and improve model accuracy
  • Regularly review the effectiveness of current rules and make necessary changes to improve accuracy
  • Build KPI Dashboards to establish, track, and measure performance against OKRs and overall fraud trends (loss rates, chargeback rates, false positives, etc.)
  • Develop an evaluation framework(s) to ‘right size’ Seller credit risk on the Fast platform
  • Conduct Seller onboarding risk reviews and support automation efforts
  • Collaborate with Engineering, Sales, and Product to build internal tools supporting Seller and Buyer payment experience
  • Identify opportunities for continuous process optimization through automation methods


  • 2+ years of experience working with data in Risk, Fraud, or Payments related role
  • Bachelor’s Degree with emphasis on CS, Mathematics, Finance, other quantitative field, or equivalent practical experience
  • Demonstrated proficiency with SQL, R and/or Python
  • Familiarity with data analysis, data pipelining, and visualization tools (e.g. Snowflake, Rockset, Looker, Mode)
  • Resourceful and ready to roll up their sleeves - no task or issue is too big or small
  • Naturally curious, idea generator, and problem solver
  • Demonstrates care and empathy towards customers and teammates

Preferred Qualifications

  • MBA, MS or other advanced degree
  • Familiarity with A/B testing and statistical modeling/forecasting
  • Computer Science degree or equivalent tech education (Lambda School, Hack Reactor, etc.)
  • Experience working in a global payment processing or dual-sided marketplace environment

Benefits of life @ Fast

  • Fast Flex allows all of our employees to choose where they want to work: our office (when open), their home or any place else in the world.
  • Early stage well-funded company with innovative engineering and product culture
  • Inclusion and diversity as a company priority
  • Competitive compensation packages
  • Comprehensive benefits (including 99% of healthcare cost and 401k matching)
  • Home office reimbursements and snack deliveries (and awesome swag!)