Senior Data Scientist / Analyst, Risk

Polymarket

$150K — $180K *
Finance & Insurance
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 7+ years in risk, fraud analytics, or investigative analytics roles
  • Expert proficiency in SQL for data analysis
  • Strong pattern recognition skills for user behavior
  • Experience in building detection models and rules
  • Ability to balance controls with user impact
  • Discretion in handling sensitive compliance findings
  • Adaptability in fast-paced environments
  • (Plus) Knowledge of on-chain analysis or blockchain forensics
  • (Plus) Familiarity with trade surveillance or AML
  • (Plus) Background in statistics or machine learning techniques
  • (Plus) Experience in fintech or data-intensive financial products

Responsibilities

  • Investigate and quantify abuse across the user funnel
  • Build detection logic using on-chain and behavioral data
  • Turn investigations into automated monitoring and alerts
  • Analyze financial exposure of abuse to prioritize actions
  • Collaborate with product to implement user verification controls
  • Support compliance with investigation analysis and reporting
  • Work with analytics engineers to ensure detection logic runs reliably
  • Document detection logic and rationale comprehensively

Benefits

  • Competitive salary & equity
  • Unlimited PTO
  • Full Health, Vision, & Dental coverage
  • 401k match
  • Hardware setup including MacBook Pro and accessories
Full Job Description
About the Role

Polymarket is looking for a Senior Data Scientist / Analyst, Risk to find the patterns that indicate abuse on our platform: fake and duplicate signups, farmed bonuses, collusive or manipulative trading, etc, and to turn what you find into controls that hold. You'll work closely with product and compliance, sitting between the data and the decisions about who gets to trade and under what conditions.

This is a role for someone who enjoys adversarial problems. The behavior you're looking for is actively trying not to be found, and the signal is usually in how accounts act together rather than in any single field. You'll be expected to build the detection, quantify the exposure, and make a clear recommendation about what to do about it. And you'll do it in a fast-moving environment where every new product opens new abuse vectors.

What You'll Do
  • Investigate and quantify abuse across the funnel, including multi-accounting and fake signups, bonus and promotion farming, wash trading, collusion, and market manipulation
  • Build detection logic that separates genuine users from coordinated behavior, combining on-chain, device, and behavioral signals rather than relying on any one of them
  • Turn one-off investigations into monitoring, including recurring reporting and alerting that surfaces new patterns without someone having to go looking
  • Size the financial exposure of each abuse vector so the team can prioritize by what it actually costs rather than by how alarming it looks
  • Partner with product on controls at the points of friction: onboarding, verification, bonus eligibility, and measure whether they worked without driving away legitimate users
  • Support compliance with the analysis behind investigations, escalations, and regulatory reporting
  • Work with analytics engineers to promote your detection logic into the modeled layer so it runs reliably instead of living in a notebook
  • Own documentation end-to-end - including the thresholds and rationale behind your detection logic, written clearly enough that compliance or any engineer can follow it without you in the room


What We're Looking For
  • 7+ years in risk, fraud analytics, trust and safety, or a similar investigative analytical role
  • Expert SQL. You can pursue a hypothesis across large behavioral datasets without supervision
  • Pattern recognition instinct. You can look at a cluster of accounts and articulate what they share and why it is unlikely to be coincidence
  • Experience building detection rules or models, and honesty about the tradeoff between false positives and missed abuse
  • Sound judgment about user impact. You understand that every control has a cost to legitimate users, and you can weigh the two
  • Comfort working alongside compliance, and the discretion to handle sensitive findings appropriately
  • Comfortable operating in a fast-moving environment where business logic changes frequently and you need to keep pace
  • (Plus) Experience with on-chain analysis, wallet clustering, or blockchain forensics
  • (Plus) Experience with trade surveillance, market manipulation detection, or AML
  • (Plus) Statistical or machine learning background - anomaly detection, graph analysis, or clustering in Python or R
  • (Plus) Experience in fintech, crypto, prediction markets, or other data-intensive financial products
Benefits
  • Competitive salary & equity
  • Unlimited PTO
  • Full Health, Vision, & Dental coverage
  • 401k match
  • Hardware setup: new MacBook Pro, big display, & accessories

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