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Experian

Expert Data Scientist, AI Fraud Applications

Experian is hiring an Expert Data Scientist, AI Fraud Applications. Level rates it ; you can apply on Experian.

Level's read on this job

  • Level rates this data scientist role Builds AI ●●●●: the job is building AI systems.
  • The posting mentions AI agents among its tools and skills.
  • Level classes it as a senior role.
  • Experian has 393 other open roles on Level.
  • Posted in the last few days.

AI in this role

ai-agents

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.

At Experian, we believe great work happens when people come together. We're focused on attracting talent in and around our designated hub locations who are open to collaborating with colleagues in person. Aligning employees to these talent markets helps foster collaboration, strengthen team connections, and support long-term career growth within Experian. This is a hybrid position and you will reside in or near one of our collaboration hubs:

Costa Mesa, San Diego & San Jose, CA · Allen & Austin, TX · Franklin, TN · New York, NY · Schaumburg, IL · Washington, DC · Atlanta, GA · Boston, MA · Seattle, WA

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 are looking for an Expert Data Scientist to help develop analytics and AI solutions for financial services, e-commerce, and other data-rich digital businesses. You will combine data science fundamentals with exploration and experimentation.

You will work across Analytics, Product, and Engineering to identify opportunities, shape the data strategy needed to support them, develop and evaluate new approaches, and help move promising concepts from idea to prototype. This is an individual contributor position and you will report into the Sr. Manager of Fraud Analytics

What You'll Do

  • Apply advanced statistical, machine-learning, and analytical techniques to complex business problems.
  • Translate ambiguous business problems into structured hypotheses, experiments, models, and prototypes.
  • Identify new opportunities where data science and new AI technologies can create value.
  • Help shape data strategy for new analytics and AI capabilities by identifying the data, derived features, and data assets needed to support experimentation, development, and scalable solutions.
  • Prototype and evaluate new approaches, comparing them with existing methods and identifying both strengths and failure modes.
  • Develop evaluation criteria covering model or solution quality, reliability, value, operational practicality, and risk.
  • Partner with Product, Engineering, and business teams to move promising analytical concepts toward practical applications.
  • Stay current with new technologies, including generative and agentic AI, and evaluate their applicability to business problems.
  • Share insights, mentor junior members of the team and help build a culture of experimentation, innovation, and learning.
  • Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Economics, or a related quantitative discipline, or equivalent relevant experience.
  • 5+ years of professional experience in data science, machine learning, statistical modeling, or advanced analytics consistent with a senior-level role.
  • Hands-on programming experience with Python and SQL.
  • Experience developing and evaluating statistical or machine-learning solutions using large datasets.
  • Experience translating business problems into analytical solutions, models, proofs of concept, or prototypes.
  • Experience in financial services, e-commerce, fraud, identity, credit risk, decisioning, or other data-intensive digital environments.
  • Experience developing prototypes, analytical tools, or new capabilities beyond traditional model development.
  • Exposure to generative AI, LLMs, AI agents, or other new AI technologies
  • Experience with modern cloud analytics platforms.
  • #LI-Hybrid

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 a 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.

How we rate this

Expert Data Scientist, AI Fraud Applications at Experian rates 84 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agents

Also common in data scientist jobs at this level

Pay

Typical data scientist job
$166k

This posting doesn't list pay. Use the typical data scientist figure when pay comes up. See data scientist jobs

Questions you could be asked

  1. How do you decide when an AI agent can act on its own versus asking for approval first?
  2. How would you decide a model or AI system is ready to ship?
  3. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: AI agents. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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