Head of Applied Machine Learning - Application Fraud

Required

• 10+ years of industry experience applying machine learning or statistics to real-world problems, or 7+ years with a relevant PhD, including 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, plus experience writing production-quality Python code and tests.
• Strong practical ML and applied statistics knowledge: able to scope solutions quickly with standard tooling and go deep where it pays off.
• Very strong end to end, with a track record of owning a technical domain and driving it to measurable business impact: planning, defining success criteria, getting buy-in, building the solution, and delivering it, whether in production, in a deck, or as strategy.
• Fluent with modern LLMs and AI-assisted development workflows, and opinionated about where they help and where they don't. Sound judgment when working with sensitive data under real information security and data governance constraints.
• Excellent communicator, including with senior leadership and cross-functional stakeholders. Detail oriented and thoughtful, someone we can rely on to make business-changing decisions while thriving on varied, open-ended, high-impact problems.
• Candidates must be legally authorized to work in the United States and must live in the United States.