Remote-first senior role in fraud risk detection with Experian Information Solutions, focused on building machine learning models and features that identify high-risk activity while minimizing friction for legitimate customers. You will work across research and engineering to take findings and turn them into production-ready tools, supported by a team that emphasizes model governance and responsible analytics.
What you’ll do
- Explore complex datasets, with guidance from senior team members, to identify fraud patterns, attack methods, and behavioral signals.
- Collaborate with senior data scientists to translate fraud questions into testable hypotheses.
- Build machine learning models for fraud detection across account opening, account takeover, and identity risk.
- Evaluate models using both technical and business metrics, including 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 partner with engineering to bring models and features into production.
- Work with the score monitoring team to set up model and feature monitoring, and support research on related client questions.
- Prepare analyses and communicate findings to both technical and nontechnical audiences.
- Apply Experian standards for data privacy, model documentation, explainability, validation, and governance.
Requirements
- 3+ years of experience in data science, machine learning, statistical modeling, or a related quantitative field.
- Bachelor’s or advanced degree in a quantitative discipline (computer science, statistics, mathematics, economics, engineering, data science, or similar).
- 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.
- Experience with tools such as pandas, NumPy, and scikit-learn.
- An investigative mindset to move from unusual data patterns to testable hypotheses.
- Familiarity with PySpark and large-scale data tools and cloud platforms such as Amazon Web Services, Google Cloud, Azure, Databricks, Snowflake, or similar.
- Exposure to financial services, FinTech, payments, or another regulated or fraud-intensive industry via coursework, internship, or prior work.
Tech stack
Python, pandas, NumPy, scikit-learn, PySpark, Amazon Web Services, Google Cloud, Azure, Databricks, Snowflake
Benefits
- Great compensation package and bonus plan
- Core benefits including medical, dental, vision, and matching 401K
- Flexible work environment: remote, hybrid, or in-office
- Flexible time off including volunteer time off, vacation, sick, and 12 paid holidays
- Explore additional benefits: https://yourexperianbenefits.com/cand-index.html
Role context: Experian’s Fraud Analytics & Commercialization includes client engagement analytics, scalable and custom analytics for financial institutions, fraud analytics consulting, and solution integrity and enablement for production-ready platforms. This is a remote role reporting into the Sr. Manager of Fraud Analytics.
Location: United States (remote) Â |Â #LI-Remote
