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Data Scientist – Fraud Detection (m/f/d)

Open 26d

Summary

Build and improve machine learning models to detect fraud in transactional and behavioral data using Python, SQL, and cloud tools, then integrate results into PAYBACK’s systems.

Role Overview

We are looking for a hands-on Data Scientist to support our fraud recognition project.
The role owns the data science and machine learning aspects of the solution, from data analysis to model evaluation.

The role is well suited for colleagues with strong analytical, SQL, Python, or software backgrounds who want to grow into a machine‑learning‑focused position.

Your responsibilities:

  • Analyze transactional and behavioral data to identify fraud patterns; perform data quality checks and exploratory analysis

  • Prepare and document datasets for training, validation, and testing using SQL and Python

  • Design fraud-relevant features and translate business logic into measurable signals

  • Develop, evaluate, and improve supervised and unsupervised ML models for fraud detection

  • Handle imbalanced, noisy real-world data and assess models using fraud-relevant metrics

  • Analyze false positive / false negative trade-offs and provide model explainability (e.g. SHAP)

  • Collaborate with developers and database teams to integrate ML outputs into the application

  • Communicate results clearly to technical and non-technical stakeholders, including the customer

Your Profile:

  • Strong Python for data analysis and machine learning (e.g. pandas, scikit-learn)

  • Advanced SQL for analytical queries and feature generation

  • Strong analytical and structured working style

  • Experience with supervised learning as well as unsupervised methods such as clustering, outlier detection, or semi-supervised approaches

  • Good understanding of overfitting, regularization, feature or label leakage, and its mitigation

  • Hands-on exposure to validation strategies under production conditions

  • Experience with cloud-based ML software stack

  • Communication skills to understand business needs and generate business value

  • Nice to Have

  • -Experience with AWS Stack

  • -Familiarity with fraud-specific metrics or cost-sensitive modeling

  • -Experience with Generative AI (e.g. for experimentation, exploration, or documentation)

  • -Basic understanding of software engineering concepts and APIs

How about?

  • Employment contract?Of course. With us you do not have to worry about stable employment.

  • Benefits?We have them! Among other: corporate incentive program, sport card, private medical care.

  • Lunch card?With the cooperation extended and permanent contract, you will receive additional funds to use for meal purchases.

  • Working in a hybrid model?Of course! ! You work with us 2 days a week from home.

  • Work wherever you want?In PAYBACK you have the opportunity. Working 100% remotely, also from European countries for 15 days a year.

  • ‎Flexible working hours?Sounds great! We start working between 7 to 10.

  • Trainings?Of course. We provide training to develop hard and soft skills.

  • Convenient location?Sure! We invite you to our new office at Rondo Daszyńskiego, but we are currently also working remotely.

  • Dress code?We definitely say no. There are no rigid dress code rules in our company, sneakers are more than welcome.

  • Friendly atmosphere at work?Yes! In PAYBACK, people are the most important asset‎.

  • ‎Something is missing?Open communication is our priority, so dare to ask!‎

See also

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