Senior Data Analyst, Risk
Binance
About This Role:
As a Senior Data Analyst, Risk at Binance.US, you will be the data engine behind how we understand and reduce financial loss. You will own the analysis of payment and chargeback data end to end, digging into what actually drives net loss and turning that into changes that ship.
This is a hands-on, high-impact role. You will break down fraud and loss by driver, investigate emerging trends, design experiments to test risk rule changes, and build the monitoring that keeps the Risk & Compliance team ahead of new threats. You will work closely with Risk, Payments, and Product to make sure your insights become real fixes, not just dashboards.
This role is a strong fit if you think naturally about where loss leaks in and how to stop it, you are comfortable moving fast in a lean environment, and you like owning a problem from raw data all the way to measurable impact.
Core Responsibilities:
Own the analysis of user lifecycle on-platform activities from on-ramp payment (ACH/Card related), trading, to withdrawal end to end: understand what drives anomalies and net loss, surface the levers to mitigate.
Deep-dive into fraud cases and user profiles to quantify exposure, design and backtest strategies/models to manage exposures.
Design and analyze A/B experiments to measure the impact of risk rule and process changes on loss, pass rate, and customer friction.
Good plus on leveraging ML techniques to surface patterns in fraud and loss data that manual analysis would miss
Break down net loss by driver (fraud type, payment method, user segment) and track it as a core monitoring metric
Build and maintain dashboards and monitoring for all essential Risk & Compliance payment metrics, with clear alerting when trends move
Partner closely with Risk, Payments, and Product teams to turn analysis into shipped changes
Run ad-hoc analysis to investigate emerging fraud and loss trends and quantify their impact fast
Preferred Skills/Experience:
4+ years in risk analytics
Strong SQL, plus Python or R for quantitative analysis, statistical modeling.
Hands-on experience with payment / chargeback data (reason codes, net loss attribution, etc)
Solid grasp of A/B testing and experiment design (hypothesis, guardrails, readout)
Strong data visualization and dashboarding skills
Able to translate complex data into clear, actionable insights for non-technical stakeholders
Solid statistical foundation
Experience in a high-growth tech environment; fintech or crypto a plus
Ability to manage multiple initiatives simultaneously while maintaining analytical rigor and execution quality
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