Remote Credit Risk & Fraud Strategist

Leyla; South San Francisco (CA); Remote; USD 122,000 - 182,000; Full time

Benefits offered by this job

Equity

Company bonus

401(k) plan

Medical, dental, and vision

Wellness stipends

Job summary

Stripe, LLC is seeking a Risk/Fraud Strategist to analyze accounts and transactions to detect risky behavior and to scale risk processes across a growing payments landscape. You will work with Engineering, Product, Data Science and Operations to build solutions that reduce losses and improve safety for users worldwide.

We’re looking for someone with a quantitative background, 4 years in risk or fraud, and proficiency in Python, R or Stata, SQL, ML, A/B testing, and tooling like Databricks or

Qualifications

• Bachelor’s degree in a quantitative field and 4 years of risk or fraud experience.
• Experience in payments-related domains and risk management.
• Proficiency with Python, R or Stata, SQL, and data tooling.
• Experience with Jira, Asana, and project management practices.
• Knowledge of ML, predictive analytics, and A/B testing.

Responsibilities

• Analyze accounts and transactions to identify risky behavior.
• Scale risk processes for a complex payments landscape.
• Collaborate with Engineering, Product, Data Science and Operations.
• Educate Stripe users about risks and prevention.
• Challenge the payments industry status quo to enable growth.

Skills

Risk management

Fraud prevention

Trust and safety operations

Python/R/Stata

SQL

Predictive analytics

Machine learning

A/B testing

Education

Bachelor's degree in a quantitative field

Tools

Databricks

Airflow

Jira

Asana

Gantt charts

Job description

Stripe, LLC is seeking a Risk/Fraud Strategist to analyze accounts and transactions to detect risky behavior and to scale risk processes across a growing payments landscape. You will work with Engineering, Product, Data Science and Operations to build solutions that reduce losses and improve safety for users worldwide.

We’re looking for someone with a quantitative background, 4 years in risk or fraud, and proficiency in Python, R or Stata, SQL, ML, A/B testing, and tooling like Databricks or