Head of Applied Machine Learning – Application Fraud
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Job Description
Head of Applied ML leading fraud detection and identity models at SentiLink, an identity and risk solutions company. Managing scientists and driving production ML strategy across financial-risk products.
Responsibilities:
- Directly manage a team of applied ML scientists, growing from 4 to 6 by the end of 2026
- Set the engineering and modeling practices used by the team
- Own strategy and execution for the applied ML domain, including roadmap, priorities, resourcing, and results
- Mentor technically, guide modeling and architecture decisions, review pull requests, and stay current on the codebase and production systems
- Partner with senior leadership, Product, Engineering, and Risk to set priorities and deliver on aggressive timelines
- Represent the domain in product strategy discussions and help shape product direction
- Own fraud detection and identity models across data acquisition, feature engineering, labeling, model training, experimentation, deployment, monitoring, and iteration
- Research emerging fraud patterns and build ML capabilities for identity verification and financial risk
- Design analyses informing product and business decisions
- Drive AI use in the team's work and help define where AI belongs in products
Requirements:
- 10+ years of industry experience applying machine learning or statistics to real-world problems, or 7+ years with a relevant PhD
- 6+ years directly managing machine learning or data science teams across two companies or more
- Startup experience strongly preferred
- Experience leading ML or data science teams in fraud, identity, fintech, banking, financial services, payments, or adjacent risk-focused domains strongly desired, but not strictly required
- Bachelor's, Master's, or PhD in Computer Science, Statistics, Mathematics, Physics, or another quantitative discipline
- Demonstrated success developing and deploying production machine learning models
- Experience writing production-quality Python code and tests
- Strong practical ML and applied statistics knowledge
- Track record of owning a technical domain and driving it to measurable business impact
- Fluent with modern LLMs and AI-assisted development workflows
- Sound judgment when working with sensitive data under real information security and data governance constraints
- Excellent communication with senior leadership and cross-functional stakeholders
- Detail oriented and thoughtful
- Legally authorized to work in the United States
- Must live in the United States
- Technologies: Python 3, PostgreSQL, AWS, XGBoost, scikit-learn, pandas, Elasticsearch, OpenSearch, Neo4j, MLflow, Flyte, and modern LLM tooling
Benefits:
- Employer paid group health insurance for you and your dependents
- 401(k) plan with employer match (or equivalent for non US-based roles)
- Flexible paid time off
- Regular company-wide in-person events
- Home office stipend
- Equity
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