Remote Senior Fraud Data Scientist: Detection & Modeling

Experian Group; Northern (KY); Hybrid; USD 110,000 - 150,000; Full time

Benefits offered by this job

Bonus plan

Medical, dental, vision coverage

Flexible remote work environment

Job summary

Experian is seeking a Data Scientist to build fraud detection models and features that identify high-risk activity while minimizing friction for legitimate customers. You will work with senior data scientists from problem definition through feature engineering, experimentation, and deployment in a remote role reporting to the Sr.

Manager of Fraud Analytics. We collaborate across analytics, engineering, and client engagement to translate insights into production-ready solutions, while upholding

Qualifications

• 1+ years of experience in data science, machine learning, statistical modeling, or a related quantitative field.
• Bachelor's or advanced degree in computer science, statistics, mathematics, economics, engineering, data science, or another quantitative discipline
• Foundation in supervised learning, model evaluation, feature selection, statistical inference, and techniques such as classification and anomaly detection.
• Proficiency in Python, with the ability to write clean, readable, and well-tested code.
• Familiarity with pandas, NumPy, and scikit-learn.
• Investigative mindset and the ability to move from unusual data patterns to testable hypotheses.
• Familiarity with PySpark, cloud platforms such as Amazon Web Services, Google Cloud, Azure, Databricks, and Snowflake, or other large-scale data tools.
• Exposure to financial services, FinTech, payments, or another regulated or fraud-intensive industry, through coursework, internship, or prior work.

Responsibilities

• Explore complex datasets, with guidance from senior team members, to identify fraud patterns, attack methods, and behavioral signals.
• Translate fraud questions into testable hypotheses with senior data scientists.
• Help build machine learning models for fraud detection across account opening, account takeover, and identity risk.
• Evaluate models using both technical and business metrics, such as precision, recall, fraud capture rate, false-positive rate, and customer friction.
• Develop and validate features using identity, transactional, behavioral, and other available data sources.
• Write clean, well-tested code, and work with engineering to bring models and features into production.
• Partner with the score monitoring team to help set up model and feature monitoring, and support research on related client questions.
• Help prepare analyses and communicate findings to both technical and nontechnical audiences.
• Apply Experian's standards for data privacy, model documentation, explainability, validation, and governance.

Skills

Data science

Machine learning

Python

Pandas

NumPy

Scikit-learn

PySpark

Cloud platforms

Statistics

Analytical thinking

Education

Bachelor's or advanced degree in CS/Statistics/Math/Engineering/Data Science

Tools

PySpark

Databricks

Snowflake

AWS

Google Cloud

Azure

Job description

Experian is seeking a Data Scientist to build fraud detection models and features that identify high-risk activity while minimizing friction for legitimate customers. You will work with senior data scientists from problem definition through feature engineering, experimentation, and deployment in a remote role reporting to the Sr.

Manager of Fraud Analytics. We collaborate across analytics, engineering, and client engagement to translate insights into production-ready solutions, while upholding