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Computer Vision Data Scientist, Receipt Fraud

  • Remote
    • Krakow, Podlaskie, Poland
    • Krosno, Dolnośląskie, Poland
    • Lublin, Lubelskie, Poland
    • Poland, Mazowieckie, Poland
    • Poznan, Wielkopolskie, Poland
    • Warsaw, Warmińsko-Mazurskie, Poland
    • Belgrade, Beograd, Serbia
    • Aachen, Nordrhein-Westfalen, Germany
    • Augsburg, Bayern, Germany
    • Bad Homburg, Hessen, Germany
    • Baden-Baden, Baden-Württemberg, Germany
    • Bergisch Gladbach, Nordrhein-Westfalen, Germany
    • Berlin, Berlin, Germany
    • Bernau, Brandenburg, Germany
    • Chemnitz, Sachsen, Germany
    • Bramsche, Niedersachsen, Germany
    • Bielefeld, Nordrhein-Westfalen, Germany
    • Darmstadt, Hessen, Germany
    • Darmstadt, Hessen, Germany
    • Dresden, Sachsen, Germany
    • Dresden, Sachsen, Germany
    • Düsseldorf, Rheinland-Pfalz, Germany
    • Essen, Nordrhein-Westfalen, Germany
    • Frankfurt, Hessen, Germany
    • Freiburg, Baden-Württemberg, Germany
    • Geoergsmarienhütte, Niedersachsen, Germany
    • Görlizt, Sachsen, Germany
    • Göttingen, Niedersachsen, Germany
    • Greifswald, Mecklenburg-Vorpommern, Germany
    • Hamburg, Hamburg, Germany
    • Halle, Sachsen-Anhalt, Germany
    • Hannover, Niedersachsen, Germany
    • Kiel, Schleswig-Holstein, Germany
    • Karlsruhe, Baden-Württemberg, Germany
    • Heinsberg, Nordrhein-Westfalen, Germany
    • Leipzig, Sachsen, Germany
    • Koln, Nordrhein-Westfalen, Germany
    • Leverkusen , Nordrhein-Westfalen, Germany
    • Lingen, Niedersachsen, Germany
    • Magdeburg, Sachsen-Anhalt, Germany
    • Mainz, Rheinland-Pfalz, Germany
    • Mittenwalde , Brandenburg, Germany
    • Munich, Bayern, Germany
    • Münster, Nordrhein-Westfalen, Germany
    • Münster, Nordrhein-Westfalen, Germany
    • Neu-Ulm, Bayern, Germany
    • Neuruppin, Brandenburg, Germany
    • Neuss, Nordrhein-Westfalen, Germany
    • Nuremberg, Bayern, Germany
    • Osnabrück, Niedersachsen, Germany
    • Paderborn, Nordrhein-Westfalen, Germany
    • Potsdam, Brandenburg, Germany
    • Quedlinburg, Sachsen-Anhalt, Germany
    • Rimbach, Hessen, Germany
    • Rostock, Mecklenburg-Vorpommern, Germany
    • Schwerin, Mecklenburg-Vorpommern, Germany
    • Stuttgart, Baden-Württemberg, Germany
    • Ulm, Baden-Württemberg, Germany
    • Varel, Niedersachsen, Germany
    • Viechtach, Bayern, Germany
    • Warendorf, Nordrhein-Westfalen, Germany
    • Wiesbaden, Hessen, Germany
    • Wuppertal, Nordrhein-Westfalen, Germany
    • Rishon Lezion, Tel Aviv, Israel
    • Tel Aviv, Tel Aviv, Israel
    • Tel Aviv, Tel Aviv, Israel
    • Jerusalem, Yerushalayim, Israel
    +66 more
  • Engineering

Work Type: Part-time commitment with flexible hours

Job description

At TechBiz Global, we are providing recruitment service to our TOP clients from our portfolio. We are currently seeking an Junior IT Support Specialist specialist to join one of our clients' teams. If you're looking for an exciting opportunity to grow in a innovative environment, this could be the perfect fit for you.

Job Description:


1. Analyze large-scale receipt data for fraud patterns and anomalies.
2. Develop statistical methods to detect subtle inconsistencies in receipt data.
3. Design feature engineering strategies combining OCR, visual embeddings, and
behavioral signals.
4. Build and optimize ML models for fraud detection using collected data points.
5. Develop fraud scoring algorithms that combine multiple detection signals and model
outputs.
6. Implement threshold optimization strategies balancing precision and recall for different
risk levels.
7. Design comprehensive fraud scoring systems.
8. Develop weighted scoring mechanisms adaptive to fraud types and retailer patterns.
9. Create interpretable scoring frameworks for manual review teams.

Job requirements

  • 4+ years as a data scientist with experience in fraud detection.

  • Strong expertise in hypothesis testing, time series, and anomaly detection.

  • Hands-on experience with classification, ensemble methods, and deep learning (scikit-learn, XGBoost, PyTorch/TensorFlow).

  • Computer Vision - Strong experience with image processing and embedding, specifically EfficientNet and FAISS, is a plus.

  • Experience with high-volume transaction processing and real-time decision systems.

  • Knowledge of retail/e-commerce fraud patterns preferred.

  • Familiarity with document fraud techniques and anti-fraud methodologies.

  • Part-time commitment with flexible hours

  • Why join us?
    Cutting-edge tech stack including GenAI and ML
    A global team with diverse perspectives
    Flexible remote work
    Opportunity to influence product direction and company growth

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