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Senior Manager Fraud Strategy and Analytics

in 10115, Berlin, Berlin, Deutschland
Unternehmen: Raisin
Vollzeit position
Verfasst am 2026-01-28
Berufliche Spezialisierung:
  • IT/Informationstechnik
    Cyber-Sicherheit, Daten Analyst, FinTech
  • Finanz/Rechnungswesen
    FinTech
Stellenbeschreibung
Stellenbezeichnung: Senior Manager Fraud Strategy and Analytics US

Senior Manager Fraud Strategy and Analytics US

Join to apply for the Senior Manager Fraud Strategy and Analytics US role at Raisin
.

Raisin is the world's leading platform for savings and investment products. Founded in 2012, the 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 +150 trillion euro market. Raisin works with over 300 banks. Today, the platform holds over 75 billion euros in assets from around one million customers which have accrued over 5 billion euros in interest with their investments.

Team The Risk Operations team safeguards Raisin’s U.S. business by monitoring, detecting, and mitigating risks across the customer lifecycle. We manage fraud prevention, investigations, payments risk, and AML/KYC oversight. It partners closely with Product, Engineering, Compliance, and Customer Service to ensure safe and frictionless customer experiences.

As a multi-bank deposit marketplace targeting rapid growth, Raisin faces complex, evolving fraud challenges across onboarding, identity verification, bank linking, and money movement. Risk Operations is at the center of designing the strategies, controls, and analytical foundations that protect the platform at scale.

Your Responsibilities

Role seniority
- This role directly reports to the Head of Risk Operations and is a senior expert role at Raisin US. As Fraud Strategy & Analytics Senior Manager, you will build and scale Raisin U.S.’s fraud detection capabilities. You will combine strategic thinking, advanced analytics, and hands‑on data science to enhance our fraud posture while optimizing customer experience. You will work cross‑functionally to develop models, design detection rules, analyze fraud telemetry, and inform decisions across the business.

This role is foundational in building Raisin’s next‑generation fraud modeling and analytics framework, without compromising on customer experience.

Fraud Modeling & Advanced Analytics
  • Own the roadmap for fraud models across the customer lifecycle.
  • Design, implement, and deploy machine learning models (supervised and unsupervised) for anomaly detection, identity risk, behavioral analytics, and transaction monitoring.
  • Build features from device, behavioral, graph, identity, ACH/payment telemetry, and network data.
  • Partner with Engineering and Data to ensure high‑quality data pipelines for real‑time model scoring.
  • Translate model outputs into practical decision strategies (rules, thresholds, step‑up flows).
  • Evaluate and pilot next‑generation fraud technologies (e.g., behavioral biometrics, graph networks).
Fraud Strategy & Operations
  • Own and execute Raisin’s U.S. fraud strategy across onboarding, account linking, and payment flows.
  • Design and refine fraud policies, rules, controls, and escalation processes.
  • Lead fraud investigations end‑to‑end and translate findings into durable controls.
  • Build fraud KPIs, dashboards, and performance reporting for leadership.
  • Quantify fraud exposure, loss trends, and efficiency metrics to inform strategic decisions.
Risk Analytics & Controls
  • Analyze payment flows and ACH telemetry to identify systemic risks.
  • Measure control effectiveness, false positives, and customer friction.
  • Provide data‑driven insights and recommendations to leadership.
  • Financial Crime (in partnership with Compliance)
  • Support AML/KYC strategy by integrating fraud insights into onboarding and monitoring workflows.
  • Maintain customer risk profiling frameworks and enhance monitoring of high‑risk customers.
  • Work with Compliance and Partner Banks to escalation unusual activity in accordance with regulatory expectations.
Your Profile
  • 8+ years in fraud risk management, fraud analytics, fraud data science, AML/financial crime, or payments risk (fintech, digital banking, payments a strong plus).
  • Strong technical skills:
    Python, SQL, and experience with feature engineering, model development, and fraud analytics.
  • Proven ability to design, deploy, and monitor machine learning models in production.
  • Deep familiarity with U.S. fraud…
Stellen-Anforderungen
10+ Jahre Berufserfahrung
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