Senior Data Scientist II
About Wolt At Wolt, we create technology that brings joy, simplicity and earnings to the neighborhoods of the world. In 2014 we started wit…
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
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.
£45,000 – £60,000 (Glassdoor, Levels.fyi, 2025)
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