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Responsibilities
As a Senior Analyst on the Risk Analytics team, you will be the analytical engine behind our fraud prevention strategy. You will build models, run experiments, and develop tools that help us make smarter, faster decisions, reducing reliance on external black boxes and static rules. You will work closely with the Manager, Risk Analytics, owning the technical and statistical work that turns strategy into something measurable and executable. You will also be a key driver of how our team uses AI: not just adopting tools as they come, but actively building workflows, automating repetitive analysis, and thinking ahead about how AI can keep us one step ahead of increasingly sophisticated fraud.What you'll doBuild and maintain Python-based analyses, models, and data pipelines that support fraud decisioning, vendor evaluation, and internal risk scoringDesign and run statistical experiments from hypothesis through measurement and communication of results, including A/B tests on routing changes, holdout experiments, and vendor performance assessmentsDevelop and iterate on internal fraud risk models using SeatGeek transaction and vendor data; own model calibration, validation, and ongoing performance monitoringActively use AI tools including LLMs, code generation, and agentic workflows to move faster and build smarter; help define how AI gets embedded into the team's analytical processes, and identify opportunities to automate work currently done manuallyContribute to vendor performance analysis: assess score calibration, measure lift across segments, and surface findings that inform routing decisions and contract discussionsBuild and maintain dashboards and reports in Looker and Hex; develop SQL models and data views to support the team's analytical needsMonitor fraud and operations metrics, investigate anomalies, and escalate findings with a clear point of view on recommended actionsCollaborate with Risk Ops agents, the manager, and cross-functional partners in Engineering, Payments, and CX to translate analysis into actionWhat you have3+ years of experience in fraud analytics, risk, fintech, or a quantitatively demanding analytical roleStrong Python skills; you build end-to-end analyses and pipelines independently, and are proficient with pandas, scikit-learn, statsmodels, or equivalent librariesStrong SQL; you can own complex data pulls, understand warehouse structures, and build views and models that others rely onSolid statistical grounding: you can design statistically valid experiments, perform significance testing, assess model calibration, and communicate findings clearly to a non-technical audienceHands-on experience building, training, and validating classification models independently; familiarity with model evaluation methods, handling class imbalance, and translating model outputs into business decisionsGenuine enthusiasm for AI tools: you actively use LLMs and code generation in your day-to-day work, think about how to design AI-assisted workflows, and take initiative in identifying where AI can replace manual effortComfort operating in ambiguity; you are expected to define the problem as much as solve itFamiliarity with fraud vendors such as Forter, Riskified, or Sardine is a plus; experience with Looker or similar BI tools is a plusPerksEquity stakeDiscretionary annual bonusFlexible work environment, allowing you to work as many days a week in the office as you’d like or 100% remotelyA WFH stipend to support your home office setupUnlimited PTOUp to 16 weeks of fully-paid family leave 401(k) matching Student loan matching programHealth, vision, dental, and life insuranceUp to $25k towards family building, reproductive health services and Gender-affirming care$500 per year for wellness expensesSubscriptions to Headspace (meditation), Headspace Care (therapy), and One Medical$360 per quarter to spend on tickets to live eventsAnnual subscription to Spotify, Apple Music, or Amazon musicThe salary range for this role is $108,000 - $157,000 USD. This role is equity eligible. In addition, you may receive a discretionary annual bonus based on individual and company performance. Actual compensation packages within that range are based on a wide array of factors unique to each candidate, including but not limited to skill set, years and depth of experience, certifications, and specific location.
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