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Job Description

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)  |  #LI-Remote

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