Jobs › Stripe

This position has closed. Stripe removed this listing from their careers page on Oct 6, 2026. The interview prep below is still useful, and there are similar open roles at the bottom of this page.

Fraud Patterns Analyst

Stripe · Remote · 4896 Fraud Operations

Posted Sep 25, 2026 · We last checked this listing on Oct 5, 2026

Likely interview questions for this role

Written from this job description, not a generic list. Each one notes what the interviewer is really checking.

About your past

Tell me about a fraud pattern you spotted before others did. What tipped you off?

What they are checking: Whether they have real pattern recognition and curiosity rather than waiting for alerts.

Tell me about a time your analysis was wrong. How did you find out and what did you change?

What they are checking: Whether they check their own work and learn from mistakes in a high-stakes setting.

What would you do

Your new rule is blocking fraud but also some good users at a major merchant. What do you do?

What they are checking: Whether they can balance loss prevention against user impact and act quickly to tune rules.

How would you explain to a product manager why a control they want would be easy for fraudsters to get around?

What they are checking: Whether they think like an attacker and can communicate that to non-fraud partners.

A fraud attack is happening right now and you have an hour. How do you decide what to do first?

What they are checking: Whether they can triage under time pressure and stop losses before perfecting analysis.

About the work

Walk me through how you'd write a fraud rule to stop a card testing attack without blocking legitimate small purchases.

What they are checking: Whether they can design precise rules and think about false positives before deploying.

Here's a SQL problem: how would you find accounts whose decline rate jumped sharply compared with their own last 30 days?

What they are checking: Whether their SQL handles baselines, windows and per-entity comparisons, which fraud analysis depends on.

How do you measure the performance of a ruleset over time, and when do you retire a rule?

What they are checking: Whether they maintain rules actively by tracking precision, recall and drift instead of piling them up.

Explain the difference between account takeover, synthetic identity and friendly fraud, and how the signals differ.

What they are checking: Whether they know fraud typologies well enough to pick the right signals for each.

How do you test a new rule before you put it in production?

What they are checking: Whether they backtest and shadow-run rules to estimate catch rates and false positives first.

Practice this interview out loud.

Offer builds a real interview for this exact role at Stripe from your resume and this job description, asks the questions one at a time, and tells you what landed. The first one is free.

Practice this out loud

The full job description

As published by Stripe.

Who we are About Stripe 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. About the team 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. What you'll do Did you know that only around 4% of the world's GDP comes from internet commerce? At Stripe, we believe that this represents a future with almost limitless potential for innovation, creativity, and global prosperity. While the promise of a global online economy is palpable, it doesn't come without significant risk. Each day, bad actors disrupt the trust and safety of the internet and increase the barrier of entry for online businesses. Before we can fully realize the potential of a global internet economy, we must first address the burgeoning problem of fraud. 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 Who you are We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement. 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