spotixx is a Frankfurt-based European FinTech firm focusing on technology for the regulated financial sector. Founded in 2019, we have grown from a small team of 60+ members to become a dynamic, self-driven enterprise with strong relationships across the German and wider European banking sector. Our mission is to revolutionize financial crime intelligence through cutting-edge machine learning techniques.
We are bootstrapped, allowing us to set our own strategies and policies without compromising on investor timelines. The market is shifting towards our capabilities: European regulators are opening the door to cross-institutional financial crime intelligence, and we are rapidly scaling our team to meet strong inbound demand. Our expertise in fraud detection and investigative work within major banks positions us well for this growing opportunity.
As a Hands-on Data Scientist, you will play a crucial role in our fast-paced environment, where you will be passionate about applying machine learning to real-world financial crime problems. You are expected to take ownership of models from idea to production, ensuring they are accurate, robust, explainable, and scalable. You will collaborate closely with engineers and product teams, working on tasks such as developing and improving ML models for fraud detection, exploring transactional and behavioral data to identify suspicious patterns, and ensuring models are deployed to cloud platforms (GCP, Azure, or AWS) and managed throughout the lifecycle.
Your responsibilities will include:
- Developing and improving ML models for fraud detection
- Working on automated rule discovery and optimization for fraud detection
- Exploring transactional and behavioral data to identify suspicious patterns
- Owning feature engineering, model training, validation, and monitoring
- Taking models from prototype to production
- Communicating results clearly to technical and business stakeholders
Our requirements for the role include:
- A degree in Data Science, Computer Science, Statistics, Mathematics, or a related field
- 2-3 years of hands-on experience in machine learning and applied data science, preferably in fraud detection, banking, or financial services
- Proficiency in Python and SQL
- Deep understanding of classification and anomaly detection algorithms, with the ability to select, tune, and evaluate models using appropriate metrics and validation strategies
- Experience with LLMs and agentic workflows
- Familiarity with model explainability tools such as SHAP and model cards
- A structured, self-directed working style and strong communication skills
- Fluent in English; proficiency in German, including client-facing technical discussions
- Ability to work flexibly, able to split time between office and home
At spotixx, we offer:
- Attractive compensation
- Flexible hybrid work model, allowing for splitting time between office and home
- High ownership and real impact in a growing fintech
- Flat structures and short paths from idea to action
- Collaborative, international team culture
We welcome applications from all qualified people, as diversity enriches us. Your perspective matters: regardless of gender, age, origin, religion, sexual orientation, or disability. Applicants with disabilities will be given preference when equally qualified.
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