Lead a team of data scientists in developing advanced ML models for fraud and risk detection in identity verification solutions. This role requires technical leadership, end-to-end ML ownership, and strong business intuition to drive product development. Ideal candidates have 7-15 years of applied ML experience, including 4+ years managing data science teams in high-growth startups.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Head of ML (Fraud/ risk)
Remote (US)
Up to $260K + Equity
My client provides innovative identity and risk solutions, empowering institutions and individuals to transaction with confidence. We’re building the future of identity verification in the United States replacing a clunky, ineffective, and expensive status quo with solutions that are 10x faster, smarter, and more accurate.
We’ve seen tremendous traction and are growing extremely quickly. Our real-time APIs have helped verify hundreds of millions of identities, starting with financial services and rapidly expanding into new markets. We are backed by world-class investors including Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin.
We’ve earned recognition from TechCrunch, CNBC, Bloomberg, Forbes, Business Insider, PYMNTS, American Banker, LendIt, and have been named to the Forbes Fintech 50. We have also been named a 2026 FICO Industry Vanguard Decision Award Winner.
About This Role
As Head of Machine Learning, Application Fraud, you will directly manage a team of talented data scientists that build our suite of products: models that identify fraudsters and advance our growing suite of products in financial risk. In this capacity, you will be relied upon to be a technical leader, mentor, and owner of your respective domain, both for your own team and the organization.
Utilize your abilities as a strong data scientist to mentor your team, probe their understanding and challenge them to do their best work. Your team will often work on projects with high visibility and impact that require deep domain understanding, critical thinking and strong technical abilities.
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This role requires managing full-stack data scientists, whose work involves model development, analysis, and writing production code.
You yourself should share that same skillset and be interested in having end-to-end ownership in a fast-moving environment where deep domain understanding drives development and unusual insights drive our competitive advantage rather than optimization of new machine learning methodologies.
Responsibilities:
- Directly manage a team of highly skilled data scientists. Start from 2-3 and grow to 5-6.
- Act as a technical mentor that can dive deep and provide detailed direction.
- Lead planning, resourcing and communications with senior leadership, product and engineering teams.
- Develop strong business intuition and guide your team to deliver performant DS solutions on aggressive timelines.
- Develop and maintain our fraud detection models through the full model development lifespan: from data acquisition decisions through featurization, focusing labelling resources, model training, experimentation, productionalization, and monitoring.
- Research new types of fraud and develop new products around identity verification.
- Achieve success by researching / developing through iteration, integration of new data sources and inventive feature engineering.
- Write production-ready code that can be relied on for real-time decision making by our partners.
- Design, perform, and present analyses that will inform data acquisition, product development, risk operations priorities, marketing, and sales efforts.
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Role requirements
- 7 - 15 years of experience in applied ML/data science, building production models in fintech, cybersecurity, or other high stakes domains
- 4+ years managing data science/ML teams in high- growth startups (must have managed people building and deploying ML products core to the business)
- Proven track record of solving complex / high profile business problems with DS / ML solutions. (Scaled a product suite of ML models, not just one model)
- Held senior/leadership role at a fast growing startup (20- 400 people) with broad scope
- Shows great slope and career progression
- Master's or PhD in a STEM field (math, stats, CS, physics, engineering) - target top universities
- End- to- end ML: feature engineering, model training, productionalization, monitoring
- Strong software engineering abilities in Python
- Domain experience in fraud, identity verification, or financial risk
- Experience in communicating progress + outcomes to senior management / stakeholders
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Why you should join
- Identity Fraud Is A National Crisis And The Market Is Enormous – Identity theft and synthetic fraud cost the US economy tens of billions of dollars every year, and the problem is getting much more complex to solve, not easier.
What Makes This Special
- Fully remote across the US. Top 1% Team working on Hard Problems. Able to sponsor most visas. Very Data Science forward company.. Ever-evolving problems (synthetic, first-party, third-party fraud) — never stagnant, never "solved. "High visibility and high impact — projects regularly seen by senior leadership.
- No handoff to an MLE. This manager owns how the product suite grows and how the team scales; will explicitly be driving direction. Working with government agencies and fortune 500s.
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