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Senior Data Analyst - Fraud Strategy & OperationsRaisin • United States
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Senior Data Analyst - Fraud Strategy & Operations

Raisin
  • US
    United States
  • US
    United States
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À propos

Senior Data Analyst - Fraud Strategy & Operations
Lehi, Utah, United States; New York, New York, United States Raisin is the world's leading platform for savings and investment products. Founded in 2012, the FinTech connects consumers with banks in the EU, the UK and the US. This gives consumers better interest rates and banks a diversified form of refinancing. Our vision is to offer savings and investments without barriers and thus open up the global 160 trillion euro market. Raisin currently employs more than 800 people from over 75 countries worldwide. Today, the platform holds over 80 billion euros in assets from more than one million investors which have accrued over 5 billion euros in returns. Team
The Risk and Fraud Operations team plays a central role in safeguarding Raisin's business by monitoring, assessing, and mitigating risks across all operational areas. We are responsible for managing fraud prevention, detection and mitigation, investigations and recoveries, monitoring for financial crime events (AML, KYC) and implementing effective risk controls to support the company's growth. Our work bridges business, compliance, and technology—analyzing data, processes, and transactions to identify potential threats while also enabling smooth and secure customer experiences. We collaborate closely with cross-functional teams (Product, Compliance, Customer Service, and Engineering) to design and execute risk and fraud management frameworks, enhance operational efficiency, and maintain a strong culture of accountability. Your Responsibilities As the Senior Data Analyst - Fraud Strategy & Operations, you will be the driving force behind our fraud defense system. We are looking for a proven analytical mind from the financial services sector who can challenge our current thinking, build predictive fraud models, redesign existing fraud models, framework and processes. Using SQL, Python/R Ecosystems, Feature Engineering, you will dissect fraud trends, build predictive models from scratch, and implement sharp, real-time rules to prevent and detect fraud across our payment rails. This role reports to the Head of Risk and Fraud Operations and requires a highly capable and entrepreneurial individual who can balance deep technical hands-on execution with high-level strategy. Advanced Fraud Strategy & Analytics
- Uncover Trends: Conduct complex data analysis using SQL, Python and Feature Engineering to proactively identify emerging fraud patterns and system vulnerabilities before they impact the platform. - Deploy Fraud Rules: Design, test, and implement robust fraud prevention rules that successfully catch bad actors while maintaining a seamless experience for real customers. - Drive Strategy: Elevate Raisin US's capabilities by introducing industry best practices, new methodologies, and innovative fraud prevention strategies that we aren't using today. - KPIs & Dashboards: Build out data-driven dashboards to track fraud metrics, losses, and mitigation performance, presenting actionable findings directly to leadership. Model Development & Maintenance
- Build Predictive Models: Design, build, and deploy machine learning and predictive models utilizing Python to detect anomalies across the entire customer journey (onboarding, funding, and money movement). - Feature Engineering: Develop model features based on identity, device, behavioral, and transactional data. - Cross-Functional Delivery: Partner closely with Product and Engineering to integrate these models into our real-time production pipelines. AML & Financial Crime Collaboration
- Risk Profiling: Partner with the Compliance team to enhance customer risk profiling, transaction monitoring, and KYC/AML workflows. - Design low-friction, custom risk rules for identity verification, account takeover protection, and transaction monitoring. - Continuous Back-Testing: Routinely stress-test current rules against changing regulatory standards and evolving financial crime tactics. Your Profile Financial Services Background:
8+ years of experience in fraud risk management, analytics, or financial crime specifically within fintech, retail banking, or digital payments. Master of Analytics:
Exceptional analytical capabilities are your biggest asset. You love diving into raw data to solve complex puzzles. Technical Stack:
Highly proficient in SQL and Python for data manipulation, analytics, and building predictive models. Experience building out fraud dashboards is a must. Payment System Domain Expertise:
Deep understanding of Deposits and ACH is required; direct experience with modern instant payment systems like RTP and FedNow is highly preferred. Rule & Model Builder:
Proven track record of designing custom fraud rules and deploying machine learning or statistical models in a live environment. Join our mission, join our team – and grow with us! At Raisin, we care about each other and it is one of our top priorities to foster an open and caring environment in which everyone feels welcome and comfortable. Our culture is strongly driven by our ambitious team, which connects more than 75 different nationalities. As part of our team, you will benefit from: Flexible working hours and up to 28 days PTO accrued from your first month, plus 13 public holidays. Employee Development Budget of $2,200 and 4 full training days per year. Company 401k contribution of 5%. Healthcare coverage contribution, including medical, dental and vision. Commuter benefits and flexible working from home policy. Regular team events and yearly Summer and Winter Party. Salary Range $120,000 - $140,000 USD Raisin Applicant Privacy Policy We value diversity and the unique experiences each individual brings. If you're excited about this role but don't meet every requirement, we still encourage you to apply. We are an equal opportunity employer and are committed to creating an inclusive environment for everyone, regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, or gender identity.
  • United States

Compétences linguistiques

  • English
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