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Full-time
bachelor degree
Attractive Compensation, Flexible Hybrid Work Model, High Ownership, Flat Structures, Collaborative International Team Culture
Posted 67d ago
~40 hrs/week
Responsibilities
Develop and optimize machine learning models for fraud detection and automated rule discovery. Manage the full model lifecycle from prototype to production, including feature engineering and monitoring.
Requirements
Requires a degree in a quantitative field and 2-3 years of experience in applied data science, preferably within financial services. Proficiency in Python, SQL, and cloud deployment is essential, along with professional fluency in English and German.
Full job description
spotixx is a Frankfurt-based European FinTech building technology for the regulated financial sector. Founded in 2019, we are a 60+ people team with deep, established relationships across the German and wider European banking sector, built on years of fraud investigation and insights work delivered inside major banks.
We are bootstrapped and set our own strategy and our own policies, without the compromises of chasing investor timelines. The market is moving toward us: European regulators are opening the door to cross-institutional financial crime intelligence, and we are scaling the team rapidly to meet strong inbound demand.
Tasks
We are looking for a hands-on Data Scientist who is passionate about applying machine learning to real-world financial crime problems. You enjoy working with complex transactional data, take ownership of models from idea to production, and care about building solutions that are not only accurate but also robust, explainable, and scalable. You are comfortable working in a fast-growing scale-up and collaborating closely with engineers and product teams.
Your responsibilities
Develop and improve ML models for fraud detection
Work on automated rule discovery and optimization for fraud detection
Explore transactional and behavioral data to identify suspicious patterns
Own feature engineering, model training, validation, and monitoring
Take models from prototype to production
Communicate results clearly to technical and business stakeholders
Requirements
Your profile
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, ideally in fraud detection, banking, or financial services
Strong 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
End-to-end ownership: from exploring high-dimensional data and building models to visualizing results, deploying to cloud platforms (GCP, Azure, or AWS), and managing the full model lifecycle
Experience with LLMs and agentic workflows
Familiarity with model explainability tools such as SHAP and model cards
Structured, self-directed working style and strong communication skills
Fluent in English; professional working proficiency in German, including client-facing technical discussions
Benefits
What we offer
Attractive compensation
Flexible hybrid work model, allowing you to split your time between our office in Frankfurt and working from home
High ownership and real impact in a growing fintech
Flat structures and short paths from idea to action
A 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.
Related keywords
Data ScienceFinTechMachine LearningFraud DetectionPythonSQLAnomaly DetectionGCPAzureAWSLLMsAgentic WorkflowsSHAPModel CardsFinancial Crime IntelligenceClassification Algorithms
spotixx, established in 2019 by financial crime experts, is at the forefront of financial crime detection.
Our AI and Machine Learning-driven solutions provide streamlined access to AML and Fraud Analytics. We pride ourselves on delivering fully automated, personalized detection models that are always up-to-date.
By securely processing pseudonymized transaction data, we enable banks to stay ahead of emerging threats.
Committed to innovation and data privacy, spotixx collaborates with universities and adheres to GDPR regulations, ensuring the highest standards of security and integrity.
Data protection https://spotixx.com/datenschutz/ and imprint https://spotixx.com/impressum/
Offices: Mainzer Landstraße 158, Frankfurt am Main, 60327, DE
AMLFighting Fraud with AIFraud Detection and PreventionsafeAMLDatasecurityDataprotectionResearch and InnovationBankingFraud Detection
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