Remote Fraud Risk Data Scientist

SmartRecruiters, Inc.; Northern (KY); Hybrid; USD 104,000 - 180,000; Full time

Benefits offered by this job

Bonus plan

Medical, dental, vision

401K matching

Flexible work environment (remote/hybr

Job summary

Experian is seeking a Data Scientist for Fraud Analytics & Commercialization. The role focuses on building fraud detection models and features to identify high-risk activity while minimizing friction for legitimate customers. You will collaborate with senior data scientists and engineers from problem definition to deployment, delivering production-ready solutions.

The position reports to the Sr. Manager of Fraud Analytics and is remote, with a strong emphasis on research, experimentation, and

Qualifications

• At least 3 years of experience in data science, ML, or a related quantitative field.
• Bachelor’s or advanced degree in computer science, statistics, engineering, data science, or another quantitative discipline.
• Direct experience developing fraud-detection, identity-risk, credit-risk, financial-crime, or other adversarial risk models.

Responsibilities

• Investigate large datasets, including exploratory analysis and fraud label development, to identify latest fraud patterns, attack methods, and behavioral signals.
• Translate ambiguous fraud and risk problems into clear hypotheses, analytical plans, model requirements, and measurable success criteria.
• Develop machine learning models for fraud detection across account opening, account takeover, and identity risk.
• Evaluate models using metrics like ROC/AUC/KS/Gini, precision/recall, fraud capture rate, false-positive rate, customer friction, and fraud losses prevented.
• Develop and validate predictive features using identity, transactional, consumer credit history, device, behavioral, temporal, velocity, network, and third-party data.
• Write clean, efficient, well-tested Python and PySpark code, and collaborate with teams to bring models and features into batch, retro, or real-time decisioning environments.
• Monitor feature quality, model performance, population changes, and fraud-pattern drift
• Design and present analyses for model behavior, tradeoffs, risks, and recommendations
• Follow appropriate standards for data privacy, model documentation, explainability, validation, and governance.

Skills

Python

PySpark

Fraud detection experience

Model deployment

Experimentation

Data visualization

Education

Bachelor’s or advanced degree in CS, statistics, engineering, data science

Tools

Pandas

NumPy

scikit-learn

XGBoost

TensorFlow

Job description

Experian is seeking a Data Scientist for Fraud Analytics & Commercialization. The role focuses on building fraud detection models and features to identify high-risk activity while minimizing friction for legitimate customers. You will collaborate with senior data scientists and engineers from problem definition to deployment, delivering production-ready solutions.

The position reports to the Sr. Manager of Fraud Analytics and is remote, with a strong emphasis on research, experimentation, and