Senior Data Scientist

Join our team as a Senior Data Scientist, where you will be responsible for the development, operationalization, and maintenance of Machine Learning models in collaboration with business stakeholders. You will work on various aspects of data preparation, feature engineering, model selection, deployment, and continual learning. Additionally, you will have the opportunity to mentor and share knowledge with team members. Enjoy a range of benefits including a learning and development budget, remote working allowance, and additional vacation days.

• Development, operationalisation and maintenance of Machine Learning models in collaboration with business stakeholders.
• Training data preparation, feature engineering operations, model selection, experimentation, and training of models.
• Model deployment, prediction servicing, and setting up automated pipelines for continual learning.

• Proficiency in data science libraries (pandas, polars, numpy, scikit-learn) and gradient boosting frameworks (XGBoost)
• Very strong communication skills, to both technical and non technical members and ability to explain complex statistical outputs to non technical officers
• Comfortable working with AI tools, thinking critically about AI outputs, and contributing to a culture of responsible AI use. We expect you to demonstrate comfort with AI-assisted workflows and a willingness to continuously develop their AI capabilities as the technology evolves
• Excellent English language skills, and preferable German language skills
• Ability to mentor and inspire team members
• Depending on your level of experience, your responsibilities and scope of role will range. We don’t care much about fancy titles, but rather about real personal and professional development, as laid out in our learning framework. Let’s figure together out how you can contribute to our team
• Adversarial & Skeptical mindset
• Minimum 6 years experience in a role of data scientist in a fast pace environment and regulated industry
• Recognize differences in typologies, spotting anomalies and understanding chargeback and dispute cycles
• Understand transactions movement, payment payload and authentication protocols
• Good knowledge of data transformation and data orchestration tools, ideally dbt and airflow
• Velocity Features, Device Dynamics and Entity Profiling
• Crisis communication under pressure in periods of unplanned situations
• Ability to grasp new business concepts and translate them into technical requirements
• Degree in Computer Science, Applied Mathematics, Statistics, Quantitive Finance and targeted Financial Engineering courses
• Payment, Fraud and Risk Domain Expertise:
• Financial and Regulatory Guardrails
• Experience working with centralized feature platforms (e.g., Snowflake Feature Store, Feast, Tecton) to prevent train-serve skew
• Adaptability and continuous learning
• Advanced SQL skills (window functions, query optimisation) and hands on experience in analytical platforms (ideally Snowflake by utilising snowpark)
• Solid understanding of software engineering principles, including version control (Git), CI/CD, and automated testing