Staff Product Data Analyst, Fraud & Surveillance

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JOIN US ON OUR MISSION TO BECOME THE #1 RETAIL TRADING PLATFORM IN THE WORLD
Welcome to the dynamic world of NinjaTrader! As an industry-leading trading platform and futures broker, we're empowering traders to take control of their financial destiny. How do we do it? We provide cutting-edge products and services that enhance the trading journey. Whether a seasoned pro or just starting out, NinjaTrader equips traders with award-winning software and brokerage services to navigate the world's leading financial markets with confidence.
Our growth story is nothing short of exhilarating. Since 2003, NinjaTrader has been dedicated to understanding and supporting traders on their journey toward trading triumph. Through those efforts, our user base has grown to over 2 million users and we have become the number one rated futures brokerage worldwide.
But we're not stopping there. We're constantly evolving, pushing boundaries, and modernizing the futures industry. Our commitment to innovation means users will always have access to dynamic tools, real-time support, and a community of like-minded traders.
So, why work at NinjaTrader? Here, you're not just part of a team; you're part of a movement. We empower employees to reach new heights in their careers by providing a dynamic culture focused on social connection, professional development, and employee recognition initiatives. Sounds too good to be true? Take it from our employees.
Join us as we redefine what's possible in trading, advocate for our customers, and continue our journey toward becoming the world's top retail-focused trading platform in the world.
What you'll do:
NinjaTrader's Trade Surveillance team is being built to protect the integrity of our markets and our partners' programs by catching fraud and abuse before it costs anyone money. As a Staff Product Data Analyst, you'll own building and maintaining the in-house detection layer — the models and rules that flag wash trading, collusion, and eval/prop-firm fraud across our trading data — and the partner-facing surveillance reports built on top of them. Engineering builds the data pipeline; you define what runs through it, applying market-structure judgment to turn raw fills into defensible fraud findings that partners and leadership can act on.
In this role you will:
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
What you'll need:
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 (BigQuery and Athena preferred), and 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, ideally in trading, fraud, risk, fintech, or market surveillance
Ability to maintain data quality and turn technical findings into clear, concise reporting for partners and executives
Bonus Points for: