Data Scientist - Fraud Risk
At a glance
Mid-level Data Science role at Rain. New York · full-time · $190,000–$230,000 base.
dataroles summary, based on the employer's posting.
What you'll do
- Build dashboards and reports that track fraud performance and support business decisions
- Set up live fraud-signal monitoring and alerts, then define the thresholds that trigger them
- Develop and test risk controls with predictive models, using both real-time and offline data
- Balance fraud loss reduction against customer friction and margin, and explain control value to go-to-market teams
- Translate complex findings for leaders and nontechnical audiences, and help partners investigate fraud concerns
What you bring
- At least three years building automated fraud strategies and running experiments such as A/B tests
- Hands-on use of SQL and Python, plus experience maintaining fraud metrics and dashboards
- A quantitative bachelor's degree or higher, such as in statistics, mathematics, engineering or computer science
- You can work through unclear problems independently and set priorities for your workload
Who this fits
This suits a data scientist with practical fraud strategy and predictive modeling experience who can communicate analysis to both technical and nontechnical partners. The role is listed in New York as onsite.
From the employer
About the Company
Rain makes the next generation of payments possible across the globe. We’re a lean and mighty team of passionate builders and veteran founders. Our infrastructure makes stablecoins usable in the real-world by powering card transactions, cross-border payments, B2B purchases, remittances, and more. We partner with fintechs, neobanks, and institutions to help them launch solutions that are global, inclusive, and efficient. You will have the opportunity to deliver massive impact at a hypergrowth company that is funded by some of the top investors in fintech, crypto, and SaaS, including Sapphire Ventures, Norwest, Galaxy Ventures, Lightspeed, Khosla, and several more. If you’re curious, bold, and excited to help shape a borderless financial future, we’d love to talk.
Our Ethos
We believe in an open and flat structure. You will be able to grow into the role that most aligns with your goals. Our team members at all levels have the freedom to explore ideas and impact the roadmap and vision of our company.
About the Team
The fraud risk management team at Rain creates sophisticated, scalable risk mitigation solutions to protect our customers and provide them a low-friction experience. We achieve this by maintaining transaction and lifecycle event monitoring, building alerts to speed up fraud detection and response, and creating risk rules and strategies empowered with ML models. We are a pillar of the business supporting new products and ensuring their success. Rain’s next generation payment technology brings unique and new fraud vectors requiring holistic, end-to-end thinking, strong data fundamentals and fraud management savvy to combat.
What you’ll do
Own the metrics, dashboards, and reports that inform business strategy and decision-making
Design and implement real-time monitoring systems for fraud signals and alerting thresholds
Design, simulate, and implement real-time risk controls using real-time and offline predictive ML models
Balance risk controls with customer experience by focusing on loss savings, reduced user friction, and margin improvement
Partner with go-to-market teams to demonstrate the technical and business value of risk controls to customers
Effectively summarize complex analytical results to leadership and non-technical stakeholders
Assist partners when they have fraud concerns with their traffic
What we're looking for
Advanced proficiency in SQL and Python
3+ years hands-on experience working on automated fraud risk strategies and experimentation (A/B tests), including implementation of real-time and offline predictive ML models
Skilled in designing, building, and maintaining dashboards and fraud risk metrics
The ability to manage ambiguous problems and find solutions
High autonomy, including the ability to prioritize your workload effectively
Relevant quantitative bachelor’s (or higher) degree (Statistics, Mathematics, Engineering, Computer Science, etc.)
Nice to have, but not mandatory
Experience at a high-growth fintech company or financial services company
Exposure to customer-facing or GTM-facing analytics or fraud issue triaging
Background in identity risk, AML, payments fraud, or compliance analytics
Fluency in AI-assisted data analysis / data science tooling
Things that enable a fulfilling, healthy, and happy experience at Rain:
Unlimited time off 🌴 Unlimited vacation can be daunting, so we require Rainmakers to take at least 10 days off.
Flexible working ☕ We support a flexible workplace. If you feel comfortable at home, please work from home. If you’d like to work with others in an office, feel free to come in. We want everyone to be able to work in the environment in which they are their most confident and productive selves. New Rainmakers will receive a stipend to create a comfortable home environment.
Easy to access benefits 🧠For US Rainmakers, we offer comprehensive health, dental and vision plans for you and your dependents, as well as a 100% company subsidized life insurance plan.
Retirement goals💡Plan for the future with confidence. We offer a 401(k) with a 4% company match.
Equity plan 📦 We offer every Rainmaker an equity option plan so we can all benefit from our success.
Rain Cards 🌧️ We want Rainmakers to be knowledgeable about our core products and services. To support this mission, we issue a card for our team to use for testing.
Health and Wellness 📚 High performance begins from within. Rainmakers are welcome to use their card for eligible health and wellness spending like gym memberships/fitness classes, massages, acupuncture - whatever recharges you!
Team summits ✨ Summits play an important role at Rain! Time spent together helps us get to know each other, strengthen our relationships, and build a common destiny. Expect team and company off-sites both domestically and internationally.
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