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 conducting complex data analysis to identify & mitigate large scale distributed fraud attacks, working closely with fraud strategy/detection/data science to implement mitigations, and working collaboratively with fraud stakeholders to expand automated detection of fraudulent merchants. They should have a deep understanding of fraud patterns/typologies, advanced SQL proficiency, and strong analytical abilities.
What you’ll do
We are looking for someone passionate about fighting fraud, identifying new trends/typologies, conducting complex data analysis, and has a strong desire to work 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 merchant and transaction fraud attacks.
Responsibilities
* Conduct advanced data analysis of structured and unstructured data sets to proactively identify emerging complex fraud attacks impacting Stripe and its users.
* Investigate, conduct root cause analysis, and deploy remediations to prevent future complex and distributed fraud attacks encompassing merchant fraud, transaction fraud, card testing, and local payment methods.
* Investigate and take action against anomalous clusters of merchants based on account activity, processing volume, or other risk indicators while minimizing negative impacts to Stripe users.
* Work in lockstep with engineering and data science teams to enhance automated detection and actioning of fraudulent accounts to minimize risks to Stripe and partner ecosystems.
* Respond to high priority incidents involving complex fraud schemes to quickly mitigate exposure to Stripe, its users, and financial partners.
* Utilize analytics to identify & implement initiatives to automate manual processes and workload across the organization.
* Create visualizations, dashboards, and queries to drive visibility and oversight into organization impact, performance, and loss risks.
* Utilize Stripe tools & 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.
* A minimum of three years of experience conducting advanced data analysis.
* Advanced level proficiency in SQL.
* Experience working closely with modeling, data science, and intelligence stakeholders to implement automatic & scaled controls & processes.
* Experience creating data visualizations and dashboards & presenting findings to technical and non-technical audiences, including senior leadership.
* You have 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 & solutions oriented.
Preferred qualifications
* Experience investigating and mitigating card testing and account takeover attacks.
* Experience designing fraud/risk workflows, analyst tooling, and processes/procedural workflows.
* Proficiency in Splunk, Python, and data visualization tools.
* Advanced data analysis in the fraud and risk space, preferably in payments, fintech, or banking.
* Undergraduate or advanced degree in analytics, data science, or statistics.
* Experience with clustering, classification, & link analysis.
* Experience working in fast-paced and rapidly changing environments.
Office-assigned Stripes spend at least 50% of the time in a given month in their local office or with users. This hits a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility about how to do this in a way that makes sense for individuals and their teams.
The annual salary range for this role in the primary location is €54,800 - €102,000. This range may change if you are hired in another location. For sales roles, the range provided is the role’s On Target Earnings (“OTE”) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. This salary range may be inclusive of several career levels at Stripe and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, and specific location.
At Stripe, we're looking for people with passion, grit, and integrity. You're encouraged to apply even if your experience doesn't precisely match the job description. Your skills and passion will stand out—and set you apart—especially if your career has taken some extraordinary twists and turns. At Stripe, we welcome diverse perspectives and people who think rigorously and aren't afraid to challenge assumptions. Join us.
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