Remote Senior Data Scientist, Fraud Risk Detection

Experian; United States; Remote; USD 110,000 - 180,000; Full time

Benefits offered by this job

Bonus program

Medical/dental/vision + 401K

Remote work options

Generous time off

Job summary

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

Responsibilities include exploring datasets, validating models with business metrics, and translating insights into production-ready solutions. This remote role reports to the Sr.

Qualifications

• 3+ 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 AWS, 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.

Responsibilities

• Explore complex datasets to identify fraud patterns, attack methods, and behavioral signals.
• Translate fraud questions into testable hypotheses with senior data scientists.
• Help build ML models for fraud detection across account opening, takeover, and identity risk.
• Evaluate models using precision, recall, fraud capture rate, false-positive rate, and customer friction.
• Develop and validate features using identity, transactional, behavioral, and other data sources.
• Write clean, well-tested code and collaborate with engineering to deploy models and features.
• Set up model and feature monitoring with the score monitoring team and support client questions.
• Communicate findings to technical and nontechnical audiences.

Skills

Python

Supervised learning

Model evaluation

Feature engineering

Pandas

NumPy

Scikit-learn

Hypothesis testing

Problem solving

Collaboration

Education

Bachelor's degree in a quantitative field

Master's degree (preferred)

Tools

PySpark

AWS

GCP

Azure

Databricks

Snowflake

Job description

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

Responsibilities include exploring datasets, validating models with business metrics, and translating insights into production-ready solutions. This remote role reports to the Sr.