Senior Data Scientist, Risk & Fraud Analytics (Remote)

Binance.US; United States; Remote; USD 150,000 - 230,000; Full time

Benefits offered by this job

Unlimited PTO

Mental wellness benefits

Remote-first culture

401k with employer match

Job summary

Binance.US is seeking a Senior Data Scientist - Risk to lead development of advanced risk models for fraud and financial crime across the platform. You will collaborate across Risk, Compliance, Marketing, and Product to drive data-driven insights that protect user funds and support growth.

The role requires 6+ years in data science and 3+ years in financial risk, with strong SQL and Python/R skills, and prior fintech experience preferred.

Qualifications

• 6+ years in Data Science/Analytics and 3+ years in Financial Risk.
• Proficient with SQL and expertise with R or Python.
• Experience building ML-based Fraud and Risk models.
• Experience in designing data visualizations and dashboards.
• Strong understanding of Risk Analytics and Fraud Models.
• Ability to translate complex data into actionable insights.

Responsibilities

• Build ML-based Fraud and Risk models to reduce risk-related losses and increase pass rate.
• Develop a rigorous data-driven culture within Risk & Compliance teams.
• Design and analyze A/B experiments for risk models.
• Create risk signals for detecting fraud and monitoring transactions.
• Define and improve monitoring metrics for Risk & Compliance.
• Provide technical leadership to Risk & Compliance teams.
• Build tools to automate risk-related processes.
• Conduct ad-hoc analysis to mitigate risk and fraud.
• Collaborate with Product to implement risk modules.

Skills

SQL

Python/R

ML models

Data visualization

Risk analytics

Communication

Tools

Python

R

Job description

Binance.US is seeking a Senior Data Scientist - Risk to lead development of advanced risk models for fraud and financial crime across the platform. You will collaborate across Risk, Compliance, Marketing, and Product to drive data-driven insights that protect user funds and support growth.

The role requires 6+ years in data science and 3+ years in financial risk, with strong SQL and Python/R skills, and prior fintech experience preferred.