Expert Data Modeler, Fraud Risk Detection at Experian

Department: AnalyticsSeniority in posting: senior

Compensation

$103,669 – $179,693/yr

Setup: Remote
Type: Full-time
Level: mid
Posted: Sep 25, 2026

Description

Experian is hiring a Data Scientist to develop fraud detection models and features for account opening, account takeover, and identity risk. The role involves exploratory analysis, hypothesis development, feature engineering, model training and evaluation, production deployment, monitoring, and governance. Candidates need at least three years of relevant data science or machine learning experience, a quantitative degree, and proficiency in Python and PySpark. The position is remote and reports to the Sr. Manager of Fraud Analytics.

Required Skills

Fraud detection
Feature engineering
Python
PySpark
XGBoost
Model evaluation
Model calibration

Additional Information

Minimum Education: Bachelor's or advanced degree in computer science, statistics, engineering, data science, or another quantitative discipline
Required Previous Experiences: At least 3 years of experience in data science, machine learning, statistical modeling, or a related quantitative field
Direct experience developing fraud-detection, identity-risk, credit-risk, financial-crime, or other adversarial risk models
Experience creating meaningful fraud features
Experience writing modular and tested Python and PySpark code for large datasets and distributed or cloud data systems
Experience using data science and machine-learning tools such as pandas, NumPy, scikit-learn, XGBoost, or TensorFlow
Experience navigating fraud-modeling challenges including class imbalance, delayed or incomplete labels, changing attack patterns, and model drift
Experience moving models from experimentation into production
Translation Company Name: Experian