Synced from SmartRecruiters · Sep 25

Data Scientist

ExperianUnited States, UNITED STATESPosted Sep 25, 2026
Data ScientistRemoteJunior
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Mirrored from Experian's own SmartRecruiters careers system · refreshed hourly

$83k–$143k
Compensation
414
Other open Experian roles
Sep 25
Posted
SmartRecruiters
Applicant system
Job description

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.

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.
  • 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 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

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.

View original posting on SmartRecruiters

What applying to Experian usually looks like

Based on publicly available information, candidates applying through SmartRecruiters typically begin with an online application and profile submission, often followed by an automated confirmation email. From there, applicants can generally expect an initial recruiter screening to review background and role fit, followed by additional evaluation stages that may include hiring manager conversations, technical or skills-based assessments, and panel discussions depending on the role, such as engineering, sales, or analyst positions at Experian. Some roles may also involve take-home exercises or case studies. Communication throughout the process is commonly handled via the SmartRecruiters platform or direct email, and response times vary based on team capacity and role seniority. Candidates should typically prepare to discuss their resume, relevant experience, and motivations, as the process may include multiple stages before a final decision is reached.

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Data Scientist
Experian · United States, UNITED STATES
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