Senior Data Science Manager - Fraud Detection & Risk Modeling

Our client is a fast-growing identity and risk solutions startup (Series B funded), helping institutions and individuals transact with confidence. They're rebuilding identity verification in the United States, replacing a slow, costly, error-prone status quo with solutions that are 10x faster, smarter, and more accurate.

In this role you will lead a small team of data scientists building fraud detection and financial risk models that power real-time decisions for their partners (almost all of the top 15 banks, Fortune 100 companies and government entities).

You'll own the full model lifecycle (data acquisition, featurization, labeling, training, productionalization, and monitoring) while researching emerging fraud patterns and shaping new identity verification products.

This is a hands-on leadership role: mentor a small team of full-stack data scientists, write production code yourself, guide planning and resourcing with senior leadership, and present analyses that inform product, risk, and go-to-market decisions.

Requirements

• 7–15 years in applied ML/data science, building production models in fintech, cybersecurity, or other high-stakes domains
• 4+ years managing DS/ML teams at high-growth startups, with direct ownership of ML products core to the business
• Track record scaling a suite of models (not just one), ideally in a senior/leadership role at a startup (20–500 people)

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• Strong Python and end-to-end ML skills; domain experience in fraud, identity, or financial risk
• Master's or PhD in a STEM field preferred

Details:

$230K–$260K base salary, bonus, equity, and benefits

US-based, remote (in-person optional across major US cities)

Visa sponsorship IS available

Reports to Head of Data Science

Note: People with backgrounds in LLM/gen AI-focused backgrounds, product analytics DS, or large-company-only experience without product ownership will NOT be a fit for this role.