Middesk

Data Scientist

Middesk  •  $155k - $180k/yr  •  San Francisco, CA (Onsite)  •  16 days ago
Apply
AI can make mistakes so check important info. Chat history is never stored.
67
AI Success™

Job Description

About Middesk

Middesk makes it easier for businesses to work together. Since 2018, we’ve been transforming business identity verification, replacing slow, manual processes with seamless access to complete, up-to-date data. Our platform helps companies across industries confidently verify business identities, onboard customers faster, and reduce risk at every stage of the customer lifecycle.

Middesk came out of Y Combinator, is backed by Sequoia Capital and Accel Partners, and was recently named to Forbes Fintech 50 List.

The Role

We’re building AI-driven applications that simplify customer workflows, starting with business onboarding. With our proprietary identity data and deep domain expertise, we’re in a strong position to expand into a broader set of intelligent, risk-aware products.

We’re looking for a hands-on engineer to help build the foundation for these systems. This role is less about inventing new ML algorithms and more about applying the right techniques to messy, real-world problems. You’ve worked in fraud, risk, or trust domains, and you understand how bad actors behave, how data breaks, and how to still ship reliable systems anyway.

This is a highly technical, hands-on role with broad influence over how we design, build, and scale data-driven systems at Middesk.

What You’ll Do

  • Build fraud & risk systems
    Design and ship production systems that detect and prevent fraud across KYB, trust & safety, and compliance workflows.

  • Work with messy, real-world data
    Tackle problems with extreme class imbalance, sparse signals, evolving adversarial behavior, and limited ground truth.

  • Leverage relationships in data
    Apply graph-based approaches and entity resolution techniques to uncover hidden connections and improve risk detection.

  • Improve signal & labeling
    Use a mix of heuristics, weak supervision, and modern AI tools (including LLMs where appropriate) to generate better features and labels.

  • Help scale our infrastructure
    Partner with engineering to build and evolve systems for feature generation, model training, and production deployment across multiple use cases.

What We’re Looking For

  • 4+ years of experience in fraud, risk, or trust & safety
    You’ve worked on real-world fraud or abuse problems and understand the domain deeply.

  • Experience building and shipping production systems
    You’ve deployed models or data-driven systems that power external-facing products.

  • Strong foundation in applied ML or data systems
    Comfortable working on classification problems with real-world constraints like imbalanced data, sparse signals, and changing patterns.

  • Experience with graph or relational data approaches
    Familiarity with knowledge graphs, network analysis, or entity linking is strongly preferred.

  • Hands-on and pragmatic
    You focus on impact over perfection and know how to balance speed, accuracy, and maintainability.

Middesk

About Middesk

Middesk's mission is to enable every business to access the products and services they need to grow and thrive. We believe that if we can make it easy for a business to access financial products, hire new employees, and transact with other businesses, that we increase the odds of success for that business to contribute to its community and the broader economy.

Our Identity product provides accurate, complete information that financial services companies need to make efficient onboarding decisions. Our Agent product makes it easy for employers to file with the state and federal agencies needed to establish their business across the country. Our customers include Affirm, Brex, Plaid, Mercury, Divvy, Rippling, Gusto, and others.

Based in San Francisco, CA, Middesk is backed by Sequoia Capital, Accel Partners, and Y Combinator.

Industry
IT & Software
Company Size
51-200 employees
Headquarters
San Francisco, California
Year Founded
2019
Social Media