Fraud Patterns Analyst

Fraud Analyst

Stripe is a financial infrastructure platform for businesses. Millions of companies - from the world's largest enterprises to the most ambitious startups - use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.

The Risk Operations team is looking for an experienced fraud analyst to join an industry-leading global fraud operations team. This position is responsible for writing and maintaining fraud rulesets to prevent transaction fraud, conducting data analysis to identify and mitigate fraud attacks, while minimizing impact to users, and working collaboratively with fraud, operations, and product stakeholders to proactively implement fraud strategies and controls. They should have a deep understanding of fraud patterns and typologies, advanced SQL proficiency, strong analytical abilities, and experience writing and managing fraud rulesets.

We are looking for someone passionate about fighting fraud, identifying new trends and typologies, conducting complex data analysis, and working collaboratively with peers and partners in the fraud space. This position works closely with cross-functional stakeholders across product, engineering, data science, and operations to identify and mitigate risk from complex, distributed transaction fraud attacks.

The right candidate for this role will have a minimum of five years' experience conducting advanced data analysis using SQL, preferably within the fraud space across e-commerce, payments, or cryptocurrency. Candidates should have experience writing, maintaining, and analyzing complex fraud rulesets and demonstrated success minimizing fraud losses along with impacts to users. Candidates should also have experience working closely with product teams to implement risk controls and demonstrate a deep understanding of fraud typologies, controls, and ability to mitigate fraud risk.

Responsibilities

• Build and maintain fraud rulesets to prevent transaction-level fraud losses, including ongoing monitoring and measurements of precision and recall
• Conduct advanced data analysis of structured and unstructured data sets to proactively identify emerging fraud attacks impacting Stripe and its users
• Collaborate closely with product, risk, and operations teams to proactively identify and mitigate fraud exposure
• Investigate, conduct root cause analysis, and deploy remediations to prevent future complex and distributed fraud attacks
• Investigate and take action against anomalous clusters of transactions based on account activity, processing volume, or other risk indicators while minimizing negative impacts to Stripe users
• Respond to incidents involving complex fraud schemes to quickly mitigate exposure to Stripe, its users, and financial partners
• Utilize analytics to identify and implement initiatives to automate manual processes and workload across the organization
• Create visualizations, dashboards, and queries to drive visibility and oversight into impact, performance, loss risks, and user experience
• Utilize Stripe tools and systems to enable systematic actioning of fraudulent merchants, maintaining an extremely high level of accuracy to prevent negative user experience

Minimum requirements

• A minimum of five years of experience conducting advanced data analysis and managing transaction fraud rulesets
• Advanced-level proficiency in SQL
• Experience working closely with modeling, data science, and intelligence stakeholders to implement automatic and scaled controls and processes
• Experience creating data visualizations and dashboards and presenting findings to technical and non-technical audiences, including senior leadership
• The ability to drive execution on projects working in a heavily cross-functional environment
• Creativity, a team-focused mentality, and effective problem-solving skills
• The ability and desire to question the status quo
• The ability to approach challenges from a user perspective while being pragmatic and solutions-oriented

Preferred qualifications

• Fraud experience in payments, e-commerce, fintechs, or cryptocurrency mitigating digital and card-not-present fraud
• Experience investigating and mitigating card testing and account takeover attacks
• Proficiency in Splunk, Python, Tableau, or other data visualization tools
• Undergraduate or advanced degree in analytics, data science, or statistics
• Experience with clustering, classification, and link analysis
• Experience working in fast-paced and rapidly changing environments
• Experience designing and implementing product-level fraud and risk controls