Applied Machine Learning Manager – Application Fraud

This is a fully remote position, open to applicants in United States.

📋 Description

• Lead a team of applied ML scientists, expanding from 4 to 6 by the conclusion of 2026.

• Establish the engineering and modeling methodologies utilized by the team.

• Take ownership of priorities, delivery, and outcomes for the designated area.

• Provide coaching and mentoring to team members throughout model development, experimentation, and technical decision-making processes.

• Review code and contribute to production systems as necessary.

• Collaborate with senior leadership, Product, Engineering, and Risk to prioritize tasks and deliver ML solutions.

• Communicate updates, trade-offs, and results effectively.

• Represent the domain during product strategy discussions.

• Develop and enhance fraud detection and identity models across data acquisition, feature engineering, labeling, training, experimentation, deployment, monitoring, and iteration.

• Investigate emerging fraud patterns and create ML capabilities for identity verification and financial risk assessment.

• Design analyses that inform product and business decision-making.

• Integrate AI into the team's operations and explore AI applications within products.

⛳️ Requirements

• Over 6 years of industry experience applying machine learning or statistics to practical problems.

• More than 3 years of direct experience managing machine learning or data science teams.

• Proven experience leading ML or data science teams in fraud, identity, fintech, banking, financial services, payments, or related risk-focused fields.

• Bachelor's, Master's, or PhD in Computer Science, Statistics, Mathematics, Physics, or another quantitative discipline.

• Proven track record of developing and deploying production machine learning models successfully.

• Proficient in writing production-quality Python code and conducting tests.

• Strong foundational knowledge in practical ML and applied statistics.

• Experience in planning, defining success criteria, obtaining buy-in, building solutions, and delivering measurable business results.

• Familiarity with modern LLMs and AI-assisted development workflows.

• Sound judgment in handling sensitive data within information security and data governance constraints.

• Excellent communication, mentoring, and hands-on technical skills.

• Must have legal authorization to work in the United States.

• Must reside in the United States.

🏝️ Benefits

• Employer-covered group health insurance for you and your dependents.

• 401(k) plan with employer matching.

• Flexible paid time off.

• Regular company-wide in-person events.

• Home office stipend.

• Equity opportunities.