Senior Data Analyst - Fraud Strategy & ML FinTech

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,
Fin Tech 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.

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.

• 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…