About this role.
SeatGeek is hiring a Senior Data Analyst to drive fraud prevention and risk decisioning through statistical analysis, machine learning, experimentation, and data products. The role owns Python analyses and pipelines, SQL models, fraud-model calibration and validation, vendor-performance assessments, and monitoring of fraud and operations metrics. The analyst will use AI tools, including LLMs and agentic workflows, to automate recurring work and improve analytical processes. Success requires strong independent judgment and close collaboration with Risk Operations, Engineering, Payments, CX, and leadership to convert findings into measurable actions.
Role DNA
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Job Complexity
5/5Pace & Pressure
4/5Autonomy Level
5/5Communication Load
4/5Salary analysis
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Core skills
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Sample interview questions
I would define clear success metrics such as fraud loss rate, approval rate, false-positive rate, manual-review volume, and customer friction. I would run a controlled routing or holdout experiment where feasible, segment results by transaction and customer characteristics, assess statistical significance, and compare vendor score calibration and incremental lift against the existing approach.
I would begin with a time-aware train-validation-test design to prevent leakage and use metrics suited to imbalance, such as precision-recall curves, recall at a fixed false-positive rate, expected loss, and calibration. Depending on the use case, I would use class weighting or carefully validated sampling, then set thresholds based on business costs and operational capacity rather than accuracy alone.
I would first validate the data pipeline and metric definitions, then isolate when and where the shift began. I would segment by payment method, geography, event, device, channel, vendor decision, and customer behavior to identify likely drivers, quantify the impact, and recommend immediate mitigations alongside a plan for deeper investigation.
I would establish ongoing monitoring for score distributions, approval and fraud outcomes, calibration, drift, latency, and key segment performance. I would also define retraining and review triggers, investigate deviations quickly, and maintain a feedback loop with operations teams so model performance is assessed against real-world outcomes.
I would target repeatable, low-risk tasks such as drafting investigation summaries, generating analysis scaffolding, documenting SQL, and triaging anomalies, while keeping sensitive decisions and model validation under human review. I would use approved tools, minimize exposure of sensitive data, evaluate outputs for accuracy and bias, and measure whether automation improves speed and quality.
SeatGeek believes live events are powerful experiences that unite humans. With our technological savvy and fan-first attitude we’re simplifying and modernizing the ticketing industry.
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 do
- Build and maintain Python-based analyses, models, and data pipelines that support fraud decisioning, vendor evaluation, and internal risk scoring
- Design and run statistical experiments from hypothesis through measurement and communication of results, including A/B tests on routing changes, holdout experiments, and vendor performance assessments
- Develop and iterate on internal fraud risk models using SeatGeek transaction and vendor data; own model calibration, validation, and ongoing performance monitoring
- Actively 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 manually
- Contribute to vendor performance analysis: assess score calibration, measure lift across segments, and surface findings that inform routing decisions and contract discussions
- Build and maintain dashboards and reports in Looker and Hex; develop SQL models and data views to support the team’s analytical needs
- Monitor fraud and operations metrics, investigate anomalies, and escalate findings with a clear point of view on recommended actions
- Collaborate with Risk Ops agents, the manager, and cross-functional partners in Engineering, Payments, and CX to translate analysis into action
What you have
- 3+ years of experience in fraud analytics, risk, fintech, or a quantitatively demanding analytical role
- Strong Python skills; you build end-to-end analyses and pipelines independently, and are proficient with pandas, scikit-learn, statsmodels, or equivalent libraries
- Strong SQL; you can own complex data pulls, understand warehouse structures, and build views and models that others rely on
- Solid statistical grounding: you can design statistically valid experiments, perform significance testing, assess model calibration, and communicate findings clearly to a non-technical audience
- Hands-on experience building, training, and validating classification models independently; familiarity with model evaluation methods, handling class imbalance, and translating model outputs into business decisions
- Genuine 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 effort
- Comfort operating in ambiguity; you are expected to define the problem as much as solve it
- Familiarity with fraud vendors such as Forter, Riskified, or Sardine is a plus; experience with Looker or similar BI tools is a plus
Perks
- Equity stake
- Discretionary annual bonus
- Flexible work environment, allowing you to work as many days a week in the office as you’d like or 100% remotely
- A WFH stipend to support your home office setup
- Unlimited PTO
- Up to 16 weeks of fully-paid family leave
- 401(k) matching
- Student loan matching program
- Health, vision, dental, and life insurance
- Up to $25k towards family building, reproductive health services and Gender-affirming care
- $500 per year for wellness expenses
- Subscriptions to Headspace (meditation), Headspace Care (therapy), and One Medical
- $360 per quarter to spend on tickets to live events
- Annual subscription to Spotify, Apple Music, or Amazon music
The 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.
SeatGeek is committed to providing equal employment opportunities to all employees and applicants for employment regardless of race, color, religion, creed, age, national origin or ancestry, ethnicity, sex, sexual orientation, gender identity or expression, disability, military or veteran status, or any other category protected by federal, state, or local law. As an equal opportunities employer, we recognize that diversity is a positive attribute and we welcome the differences and benefits that a diverse culture brings. Come join us!
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