Senior Data Scientist

Development, operationalisation and maintenance of Machine Learning models in close collaboration with the business stakeholders for common risk and financial protection with different latency: Fraud Protection, Compliance & AML.

What you'll do

• Development, operationalisation and maintenance of Machine Learning models in close collaboration with the business stakeholders for common risk and financial protection with different latency: Fraud Protection, Compliance & AML
• Training data preparation in close collaboration with the analytics engineers including analysis of vast amounts of transactional logs, data labelling, applying chronological splitting and sampling techniques to handle class imbalances
• Feature engineering operations including common features, cross features, positional features and building a centralised feature store
• Model selection, experimentation and training of baseline and gradient boosted models, evaluating performance and trade offs
• Model deployment and prediction servicing from batch to online in close collaboration with the data infrastructure team
• Continual learning by setting up automated pipelines that monitor population drift and continuously re-fit models on fresh data when performance drops below predefined operational baselines
• Knowledge sharing and mentoring across the team

What you'll need

• Minimum 6 years experience in a role of data scientist in a fast pace environment and regulated industry
• Proficiency in data science libraries (pandas, polars, numpy, scikit-learn) and gradient boosting frameworks (XGBoost)
• Advanced SQL skills (window functions, query optimisation) and hands on experience in analytical platforms (ideally Snowflake by utilising snowpark)
• Experience working with centralized feature platforms (e.g., Snowflake Feature Store, Feast, Tecton) to prevent train-serve skew
• Good knowledge of data transformation and data orchestration tools, ideally dbt and airflow
• Solid understanding of software engineering principles, including version control (Git), CI/CD, and automated testing
• Payment, Fraud and Risk Domain Expertise including understanding transactions movement, payment payload, authentication protocols, typologies and anomalies, chargeback and dispute cycles, velocity features, device dynamics, entity profiling, and financial and regulatory guardrails
• Very strong communication skills to both technical and non technical members with ability to explain complex statistical outputs to non technical officers

Nice to have

• Degree in Computer Science, Applied Mathematics, Statistics, Quantitive Finance and targeted Financial Engineering courses
• German language skills
• Ability to mentor and inspire team members

What they offer

• Learning & development budget of €1000 per year and transparent growth framework
• Competitive salary and variable remuneration program
• 28 vacation days, increasing by 2 days after 2 years and 3 days after 3 years
• Home office budget, monthly meal allowance, Deutschland ticket subsidy
• Opportunity to work abroad for up to 12 weeks per year