Data Science Manager, Fraud & Payments

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Data Science Manager, Fraud & Payments in the United States.

In this role, you will lead a team of data scientists responsible for developing advanced fraud detection models, optimizing payment performance, and delivering actionable insights across the commerce lifecycle. You will guide hands-on modeling efforts, standardize experimentation frameworks, and drive operational excellence while collaborating closely with cross-functional teams in fraud operations, payments strategy, finance, and engineering. The position offers the opportunity to balance fraud prevention with revenue growth and customer experience, influencing key business decisions. You will help shape the team’s technical roadmap, develop talent, and implement scalable machine learning solutions in a fast-paced, high-impact environment. This role combines strategic leadership with hands-on technical expertise to protect payments systems and enhance operational outcomes.

Accountabilities:

• Lead, coach, and develop a team of data scientists working on fraud detection, risk modeling, and payment optimization.
• Design, evaluate, and productionize machine learning models for real-time decisioning and post-transaction review.
• Build standardized experimentation frameworks, including champion vs challenger model evaluations, holdouts, and policy impact testing.
• Apply causal inference to measure the impact of controls and payment routing strategies.
• Develop automated monitoring, anomaly detection, and alerting for emerging fraud patterns and behavioral shifts.
• Partner with cross-functional teams to align objectives, drive execution, and promote adoption of shared metrics and dashboards.
• Influence business decisions by simplifying complex findings and providing actionable insights.

Requirements

• 8+ years of experience building and deploying machine learning models in production, ideally in fraud detection, risk scoring, payments, or trust & safety domains.
• 2+ years of leadership experience managing or mentoring data scientists.
• Strong programming skills in Python and SQL, with experience using ML toolkits such as scikit-learn and XGBoost.
• Hands-on experience evaluating risk controls using experimentation, holdouts, or causal inference methods.
• Ability to balance tradeoffs between fraud loss, authorization success, revenue impact, and user friction.
• Strong communication skills and ability to influence stakeholders with complex analyses.
• Preferred: experience with real-time scoring systems, streaming architectures, e-commerce, fintech, gaming, or digital marketplaces.
• Preferred: familiarity with LLM classification or graph-based detection approaches.

Benefits

• Competitive base salary: $186,000 – $279,000 USD (varies by location).
• Comprehensive health coverage, including medical, dental, and vision insurance.
• 401(k) plan with company matching.
• Generous paid time off, wellness programs, and parental leave.
• Employee discounts on products and services.
• Flexible hybrid/remote work model with opportunities for in-person collaboration.
• Opportunities for professional growth and skill development within a global, high-performing team.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly.
🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.
📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.
🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.
🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team.

Thank you for your interest!

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