Senior Fraud Data Modeling Engineer

Experian; United States; Remote; USD 80,000 - 110,000; Full time

Benefits offered by this job

Bonus plan

Medical, dental, vision

401K matching

Flexible time off

Volunteer time off

12 paid holidays

Job summary

Experian is seeking a data scientist to translate fraud questions into testable hypotheses and help build machine learning models for fraud detection across account opening and identity risk.

You will explore complex datasets, evaluate models with precision and recall, and communicate findings to both technical and nontechnical audiences. The role includes a great compensation package and bonus plan and comprehensive core benefits.

Qualifications

• 1+ years in data science or related quantitative field with a degree in computer science, statistics, or engineering.
• Foundation in supervised learning, model evaluation, and feature selection.
• Proficiency in Python and tools like pandas, NumPy, and scikit-learn.

Responsibilities

• Explore complex datasets to identify fraud patterns and behavioral signals.
• Evaluate models using technical and business metrics like precision and recall.
• Help prepare analyses and communicate findings to both technical and nontechnical audiences.
• Partner with the score monitoring team to support model and feature monitoring.

Skills

Supervised learning

Model evaluation

Feature selection

Education

Degree in computer science / statistics / engineering

Tools

Python

pandas

NumPy

scikit-learn

Job description

Experian is seeking a data scientist to translate fraud questions into testable hypotheses and help build machine learning models for fraud detection across account opening and identity risk.

You will explore complex datasets, evaluate models with precision and recall, and communicate findings to both technical and nontechnical audiences. The role includes a great compensation package and bonus plan and comprehensive core benefits.