Senior Data Science/ML Engineer - Financial Crime

Responsibilities

• Build and ship production ML systems end to end : own and evolve end-to-end batch training pipelines, model versioning, monitoring, model deployment, and rollback for transaction monitoring models.
• Build, maintain, and improve ML models for transaction monitoring, focusing on detection quality, operational efficiency, and regulatory compliance
• Engineer features mapped to AML and Fraud typologies and suspicious behaviours, working closely with Risk investigators to translate domain knowledge into alerting logic and threshold calibration
• Run sensitivity tests on synthetic datasets, produce ML governance artefacts such as model cards, and deliver audit-ready documentation to meet regulatory expectations
• Own and evolve the AML Risk Score by analysing driver contributions, monitoring drift, running back-testing, and recommending improvements to features, logic, and thresholds
• Partner with AML and Fraud Operations, Product, and Engineering to translate stakeholder needs into actionable, scalable data science solutions
• Track and improve detection performance metrics, adapt solutions to regional compliance requirements, and contribute to system design documentation
• You'll be great for this role if you have...

Requirements

• Production Python engineering : you write code that ships - you're comfortable with CI/CD, automated testing, versioning, and monitoring in a real production environment
• End-to-end ML pipeline experience : demonstrated experience deploying and operating ML models in production, including drift monitoring and rollback
• Modelling and productionalizing models: demonstrated experience training ML models, choosing appropriate KPIs and metrics for evaluation.
• Data engineering fundamentals : hands-on experience with complex, multi-source data ecosystems, data quality, and lineage
• Clear, confident communication : ability to align cross-functional stakeholders, set expectations, and turn ambiguous compliance requirements into a concrete technical plan
• Experience with Pyspark
• Experience in AML, fraud detection, or financial crime domains
• Unsupervised machine learning (e.g. anomaly detection, clustering)
• Familiarity with Feature Stores and alerting threshold calibration
• Experience producing regulatory ML governance artefacts (model cards, audit documentation)
• Experience with AI systems and tooling
• Why you should join SumUp
• 🌎 Opportunity to work with SumUppers globally on large-scale fintech products used by millions of businesses worldwide, from our Berlin office. This involves an office-first setup
• 🌈 Commitment to Diversity and Inclusion: be part of a workplace that values and promotes diversity, fostering an inclusive environment where everyone's perspectives are respected and embraced
• 🚀 Enrolment onto our Virtual Stock Option programme: you will own a stake in SumUp's future success
• 📚 A dedicated annual L&D budget of €2,000 for your individual development, which can be used to attend conferences and/or advance your career through further education
• 💶 A corporate pension scheme where we match up to 20% of your contributions
• 🏖️ Generous time off: enjoy 28 days of paid leave plus public holidays and special leave days
• 💪 Numerous other benefits such as Urban Sports Club subsidy, Kita placement assistance, and subsidised office lunches
• 🌴 Break4me: 1-month sabbatical after 3 years of service
• 🔗 Referral Bonus: earn additional rewards by referring talented individuals to join the SumUp team
• About SumUp
• Be empowered to do more that matters.
• At SumUp, we're on a mission to empower small businesses across the globe by providing simple and affordable tools that all

Benefits

Additional Information

Team description The Risk AI Engineering Squad is a cross-functional team within the Risk & Compliance tribe, responsible for developing cutting-edge data products and ML solutions that power Transaction Monitoring and protect our merchant base from Money Laundering and Financial Crime. We combine automation, AI, and engineering excellence to build innovative products that empower Risk and AML teams to work smarter, faster, and more efficiently. The Senior Data Scientist role is critical to advancing our transaction monitoring capabilities through machine learning, feature engineering, and scalable model pipelines. You will work across the full model lifecycle - from typology understanding and data exploration to feature development, training, validation, deployment, and monitoring - helping ensure our Risk and AML controls remain effective, auditable, and compliant across products and markets. We actively welcome applications from women and people from underrepresented backgrounds. Diverse perspectives make our team stronger and our systems more robust. If you're motivated by technical depth, real-world impact, and the challenge of making ML work reliably in a high-stakes environment, this role is built for you. Join us to shape the future of financial safety and make a lasting impact!

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