Staff Product Data Analyst, Fraud & Surveillance

NinjaTrader is a trading platform and futures broker that provides trading software and brokerage services. The Staff Product Data Analyst will own fraud and market-abuse detection models, rules, and partner-facing surveillance reporting, while investigating flagged cases and translating trading data into actionable findings.

Responsibilities:

• Own and evolve the detection models and rules that flag market abuse — wash trading, hedging and reverse trading, collusion and coordinated accounts — across our trading data
• Own partner-facing surveillance reporting end to end, starting with standardized end-of-day reports and evolving toward real-time monitoring
• Work directly with eval and prop-firm partners to validate true and false positives, calibrate detection quality, and tune thresholds and rules
• Collaborate with partners on custom reporting and solution feasibility for partner requests
• Translate fraud patterns into precise, tunable detection logic across matching criteria, hold-time thresholds, recurrence windows, and P&L severity scoring
• Maintain data quality and hygiene across the surveillance data that feeds detection and reporting
• Investigate flagged cases end to end and produce clear, evidence-backed findings that partners and internal leadership can act on
• Reduce false positives continuously and surface new fraud patterns as bad actors adapt

Requirements:

• Deep trade-surveillance or market-risk experience, including hands-on knowledge of market-abuse patterns such as wash trading, hedging, reverse trading, collusion, and copy trading, and how each can produce benign-looking lookalikes
• Working knowledge of futures/derivatives trading mechanics — fills, positions, and P&L — and what abusive trading looks like in practice
• Strong SQL and hands-on experience with a cloud data warehouse
• comfort investigating large, messy transactional data
• Proven ability to design detection rules or anomaly models and defend them analytically — including precision/recall tradeoffs, thresholds, and validation — with domain judgment leading the analysis
• 10+ years in data analytics or data science
• Ability to maintain data quality and turn technical findings into clear, concise reporting for partners and executives
• BigQuery and Athena preferred
• ideally in trading, fraud, risk, fintech, or market surveillance
• Master's degree in analytics or a related quantitative field
• Prior prop-firm or brokerage experience
• Python or experience with fraud, AML, or surveillance tooling
• Experience building toward real-time or streaming detection