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

Role Overview

Overview

Experian's Fraud Analytics & Commercialization operates across four main functions. These include client engagement analytics, scalable and custom analytics for financial institutions, fraud analytics consulting, and solution integrity and enablement for production-ready platforms.

We're looking for a motivated Data Scientist to help build fraud detection models and features that identify high-risk activity while minimizing friction for legitimate customers. Core skills for this role include strategic thinking, an eagerness to collaborate, and empathy. You will will dig into surprising signals in the data and to learn how that insight becomes a deployed model.

You will help investigate the latest fraud patterns, build features, and train and evaluate machine learning models. You will work with senior data scientists and engineers starting with problem definition through feature engineering, experimentation, and deployment. You will be a developing programmer, ready to translate theoretical principles into production-ready solutions.

We continue to sharpen through research and the engineering that turns those findings into tools and systems built for commercialization.

This is a remote role and you will report into the Sr. Manager of Fraud Analytics.

What you'll do

• Explore complex datasets, with guidance from senior team members, to identify fraud patterns, attack methods, and behavioral signals.
• Work with senior data scientists to translate fraud questions into testable hypotheses
• 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.

Experience and Skills

• 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 common data science and machine-learning tools such as 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.
• #LI-Remote

About Experian

Experian is a global data and technology company, powering opportunities for people and businesses around the world. We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more. Experian invests in people and new advanced technologies to unlock the power of data. We have an amazing team of 25,200 people in 32 countries.

Benefits/Perks:

• Great compensation package and bonus plan
• Core benefits including medical, dental, vision, and matching 401K
• Flexible work environment, ability to work remote, hybrid or in-office
• Flexible time off including volunteer time off, vacation, sick and 12-paid holidays
• Explore all our exciting benefits here: https://yourexperianbenefits.com/cand-index.html

Our uniqueness is that we celebrate yours. Experian's people first, inclusive and purpose-driven culture is multi award-winning. We have won World's Best Workplaces 2025 (Fortune Global Top 25), and Great Place To Work in 26 countries to name a few.

Experian's recruitment process is conducted only through authorised channels. Recruitment communications will only be sent from an @experian.com email address. Experian will never ask candidates to make any payment as part of an application, interview, assessment, onboarding, or recruitment process.

Our compensation reflects the cost of labor across several U.S. geographic markets. Within this range, individual pay is determined by work location and additional factors such as job-related skills, experience, and education. You will be eligible for a variable pay opportunity and a comprehensive benefits package.

Experian is proud to be an Equal Opportunity Employer for all groups protected under applicable federal, state and local law, including protected veterans and individuals with disabilities. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.