Head of Applied Machine Learning (ML)

About the role

SentiLink builds the fraud detection and identity verification models that power much of the U.S. financial system. As Head of Applied Machine Learning you will own a major ML domain end‑to‑end, leading a growing team of applied ML scientists while staying hands‑on with modeling and code reviews.

Key responsibilities

• Directly manage a team of applied ML scientists (4 today, expanding to 6 by 2026) and define engineering and modeling practices.
• Own the strategy, roadmap, and execution for your ML domain, including data acquisition, feature engineering, labeling, model training, experimentation, deployment, monitoring, and iteration.
• Partner with senior leadership, Product, Engineering, and Risk to set priorities and deliver on aggressive timelines.
• Research emerging fraud patterns, build new ML capabilities for identity verification, and drive AI adoption within the team.

Required profile

• 10+ years applying machine learning or statistics to real‑world problems (or 7+ years with a PhD), with at least 6 years managing ML or data‑science teams.
• Experience in fraud, identity, fintech, banking, payments or related risk domains (startup experience strongly preferred).
• Proven track record of delivering production ML models and writing production‑quality Python code and tests.
• Excellent communication skills and ability to influence senior leadership.

Required skills

• Python 3
• PostgreSQL
• AWS
• XGBoost
• scikit‑learn
• pandas
• Elasticsearch / OpenSearch
• Neo4j
• MLflow
• Flyte
• Modern LLM tooling

What we offer

• Employer‑paid health insurance for you and dependents
• 401(k) plan with employer match
• Flexible paid time off and regular company‑wide in‑person events
• Home office stipend and support for remote work