KeyStep

Senior Data Scientist

SumUp
Berlin, Germany
8 days ago
full-time

Skills & Technologies

PythonData EngineeringMachine LearningData ScienceAuditComplianceRegulatoryAMLDriftTrainingAIDocumentationRegulatory Compliance

Job Description

Team description

The AI AML Engineering Squad sits at the intersection of machine learning and financial crime prevention, building the data products and ML systems that keep SumUp's transaction monitoring effective and compliant across 37 markets. This role carries genuine ownership: you'll be responsible for the models, pipelines, and risk scoring that determine whether suspicious activity is caught, escalated, and documented in a way that satisfies regulators. If you're motivated by technical depth, real-world impact, and the challenge of making ML work reliably in a high-stakes environment, this is built for you.

What you'll do

Build, maintain, and improve ML models and batch training pipelines for AML transaction monitoring, focusing on detection quality, operational efficiency, and regulatory compliance

Engineer Feature Store features mapped to AML typologies and suspicious behaviours, working closely with AML 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 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

Strong Python skills with hands-on data engineering experience and a proven track record of building reliable, production-grade ML workflows

Experience in feature engineering and unsupervised machine learning, with the ability to translate domain knowledge into model behaviours and alerting logic

Proven abilit

Company & Role Analysis

JobSeeker+
Likely perks
Private MedicalPension25+ Days HolidayStock OptionsLearning BudgetFlexible Hours
Culture & working style

Neutral 2–4 sentence summary of what working at this company is like, drawn from public reviews and press coverage. Tone, collaboration style, pace, benefits highlights.

Market salary range

£45,000 – £60,000 (Glassdoor, Levels.fyi, 2025)

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