Senior Fraud Data Analyst - Luxembourg

Satispay; Milano; In loco; EUR 85.000 - 110.000; Tempo pieno

Vantaggi offerti da questo lavoro

Private health insurance

Relocation support

Language courses

Flexible hours

Descrizione del lavoro

Satispay is hiring a Senior Fraud Data Analyst to safeguard real-time payments and optimize risk strategies. You will design decisioning logic, translate fraud patterns into high-performing rules, and collaborate with data science to operationalise models.

Strong SQL/Python skills and a payments background are essential for success in this role. You will work with a global team to reduce fraud risk, improve detection accuracy, and report on portfolio health to senior leadership.

Competenze

• 6+ years of experience in risk, payments or credit sectors.
• Strong SQL and Python for data analysis and strategy development.
• Knowledge of real-time decisioning environments in payments.
• Fluent in English and able to communicate effectively.

Mansioni

• Architect Real-Time Strategies for our fraud detection engine.
• Develop precise rules to balance false positives and loss.
• Deconstruct payment fraud and mitigate emerging schemes.
• Optimize the decisioning stack with product and engineering.
• Calibrate ML models and heuristic rules for production use.
• Champion frictionless user experience while maintaining security.
• Provide data-driven performance reporting to leadership.

Conoscenze

SQL

Python

Fraud domain knowl

English fluency

Real-time decisioning

Strumenti

PySpark

GraphQL

Descrizione del lavoro

Please note that this opportunity requires relocation to our Luxembourg office.

About us

Traditional banking has never really given you control over your financial life. Satispay exists to change that: to empower people through finance.

That means making financial services easy and accessible for over 6.5M users. We started with payments, then benefits, investing, cards... and we’re not done. Not even close. We follow the same logic every time: find a real problem, solve it properly, then look for the next one. The destination? To build the most loved financial platform in the world. If you own outcomes rather than tasks, stay close to what users need, and refuse to wait for someone else to fix what's broken — you'll find people here who work exactly in the same way. And together, you'll build something worth being proud of.

What you'll be doing

As our Senior Fraud Data Analyst, you'll handle one of the most critical challenges in digital payments: keeping millions of transactions safe in real time.

Here's what that looks like in practice:

• Architect Real-Time Strategies – You will be responsible for our 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 (FPR) and Gross Fraud Loss.
• Deconstruct Payment Fraud – Proactively hunt for emerging schemes (ATO, social engineering) and turn these insights into end-to-end mitigation strategies.
• Optimise the Decisioning Stack – Partner with Product and Engineering to define analytical requirements for new features and third-party data signals.
• Calibrate ML & 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, designing 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 our risk appetite.

Who we're looking for

This role needs someone genuinely curious about how fraud works, and driven enough to stay one step ahead of it.

• Experience – You have at least 6 years’ experience, specifically within the risk, payments, or credit sectors.
• Technical Proficiency – You are highly skilled in SQL and Python for data analysis and strategy development.
• Domain Expertise – You have a solid understanding of payment fraud dynamics and experience working with real-time decisioning environments.
• Communication – You possess excellent communication skills and are fluent in English.
• Nice to Have – Experience with Machine Learning, Data Science, PySpark, or GraphQL knowledge is a significant plus.

Don't worry if you don't tick every box. We believe in the power of different viewpoints and strengths. Your unique perspective is important as we build something special: if you're passionate and can make a difference, we truly encourage you to apply.

CareAbout: how we support your impact

We move fast, and evolution never stops. It’s a fun ride, but it can be challenging. To make sure our people truly thrive, we’re committed to making their lives easier, both in the office and out in the world. That’s why we created CareAbout:

• Health: private insurance for you and your family, psychological support with Serenis, mental health workshops.
• Financial resources: Stock Option Plan, meal vouchers, relocation support if you’re moving countries.
• Growth and development: professional development programs, internal mobility, language courses with Preply.
• Flexibility: unlimited PTO, hybrid working policy*, flexible working hours.
• Family: enhanced parental leave, additional leave for child sickness.

*We embrace three days per week in-office (Tuesday and Thursday + 1 of your choice), with the option to request extra remote time.

Equal opportunity employer

At Satispay, we're proud to be an equal opportunity employer. We celebrate diversity and inclusion, welcoming individuals of all backgrounds. This opportunity is open to everyone, regardless - for instance - of race, colour, religion, sex, gender identity, sexual orientation, and national origin.

Join us in a workplace where everyone belongs!

Learn more about us

Curious what it's actually like here? Our values and pillars shape how we work every day: explore them here.

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