Postdoc: Interpretable ML for Financial Fraud Detection

Euraxess; Orléans; Hybrid; EUR 32,000 - 42,000; Full time

Job summary

UNIVERSITE D'ORLEANS invites a postdoctoral researcher to join Laboratoire d'Économie d'Orléans (LEO) to develop machine learning and deep learning models for fraud detection across insurance, social contributions, and banking. You will work with a multidisciplinary team and publish research in top journals.

The role requires a PhD in Data Science, ML, econometrics, finance, or statistics, strong English, and proficiency in Python or R.

Qualifications

• PhD in data science, ML, econometrics, finance or statistics.
• Strong expertise in machine learning and deep learning (ML/DL).
• Proficient programming in Python or R; experience with large-scale datasets and feature engineering.
• Familiarity with explainable AI (XAI) methods.

Responsibilities

• Develop ML/DL models for fraud detection in insurance, social contributions and banking.
• Conduct comparative studies of detection methodologies and preprocess large datasets.
• Publish 2–3 papers in peer-reviewed journals and present at major conferences.

Skills

Python

R

ML/DL

XAI

Education

PhD in Data Science/ML/Econometrics/Finance/Statistics

Tools

High-performance computing

Job description

UNIVERSITE D'ORLEANS invites a postdoctoral researcher to join Laboratoire d'Économie d'Orléans (LEO) to develop machine learning and deep learning models for fraud detection across insurance, social contributions, and banking. You will work with a multidisciplinary team and publish research in top journals.

The role requires a PhD in Data Science, ML, econometrics, finance, or statistics, strong English, and proficiency in Python or R.