Fraud Data Analyst

09 set - Turbigo
Satispay

Relocation

We are looking for a Fraud Data Analyst to work out‑of‑office in Luxembourg. This opportunity requires relocation to our Luxembourg office.

About Us

Satispay is a complete financial platform that removes friction from everyday payments. With more than 6 million users, we help people pay, save and invest in a single, seamless experience.

What You'll Be Doing

As our Fraud Data Analyst, you will secure the future of digital payments by architecting sophisticated real‑time defence strategies.

Responsibilities
- Architect real‑time decisioning strategies – responsible for the real‑time decisioning engine, designing and deploying logic that combines ML scores with velocity features to make millisecond decisions.
- Precision rule development – translate complex fraud patterns into high‑performing rules, optimising the balance between False Positive Rates and Gross Fraud Loss.
- Deconstruct payment fraud – proactively hunt for emerging schemes and turn these insights into end‑to‑end mitigation strategies.




- Optimize the decisioning stack – partner with Product and Engineering to define analytical requirements for new features and third‑party data signals.
- Calibrate ML‑and‑heuristics – work with Data Science to operationalise machine learning models, determining how to best wrap model scores with heuristic rules.
- Champion frictionless UX – analyse security measures to identify unnecessary hurdles and design dynamic friction strategies for a seamless user experience.
- Strategic performance reporting – monitor rule efficacy and portfolio health, presenting data‑driven recommendations to senior leadership to evolve risk appetite.

Qualifications
- Experience – 3 to 7 years in risk, payments or credit sectors.
- Technical proficiency – highly skilled in SQL and Python for data analysis and strategy development.
- Domain expertise – solid understanding of payment fraud dynamics and experience in real‑time decisioning environments.
- Communication – excellent

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