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Data Scientist (f/x/m)

CompraTica Empleos

EMP:Technology
Frankfurt am Main
Tiempo Completo
Remoto
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Descripción

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.

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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.

Responsabilidades

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

Requisitos

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-di...

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