Director, Fraud Analytics Consulting - Remote

• Full-time
• Employee Status:
  Regular
• Role Type:
  Hybrid
• Job Posting - Salary Range: $176,036 - $316,865
• Department:
  Analytics
• Schedule:
  
  Full Time

Experian is a global data and technology company, empowering opportunities for people and businesses worldwide. 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.

The Fraud Analytics & Commercialization team drives Experian's fraud analytics business through four integrated functions — pre-sales engagement, scalable and custom solutions, consulting, and operational enablement — with the goal of becoming the industry's provider-of-choice. The Director of Fraud Analytics Consulting will work directly with major financial institutions to co-build custom fraud detection models and help clients understand emerging fraud trends.

The role calls for an experienced data scientist with an impact-focused mindset and strong collaborative, critical-thinking, and problem-solving skills — and welcomes candidates from unconventional backgrounds who demonstrate curiosity and self-direction. In addition to client-facing analytical work, the Director will mentor and develop the team, partner with product teams to scale analytics capabilities, and foster a culture of thoroughness, empathy, and shared success.

This is a remote position. You will report to the SVP of Fraud Analytics.

You will have the opportunity to:

• Partner with major financial institutions and emerging market clients to help them realize the full potential of Experian's proprietary fraud data and analytics solutions.
• Co-develop custom fraud detection models with client teams, guiding them through the data, the analytics environment, and Experian's proprietary fraud detection methodologies.
• Conduct investigative analytics to help clients identify new fraud trends, emerging risk patterns, and evolving threats across their portfolios.
• Design and implement scalable proof‑of‑value processes, including standardized templates and automation, to support expansion into new markets and client segments.
• Build self‑serve tools and onboarding resources that accelerate time-to-value for down‑market clients and support their path to self‑sufficiency.
• Partner with product teams to shape the analytics consulting strategy for market expansion.
• Lead, mentor, and develop a small team of data scientists, creating an environment where curiosity, collaboration, and continuous growth are the norm.
• Serve as a trusted advisor and subject matter expert to clients, translating complex analytical concepts into clear, actionable insights.

• 7+ years of experience in data science, analytics, or a related quantitative field.
• Bachelor’s or Master’s degree in Statistics, Applied Mathematics, Econometrics, or a related quantitative discipline – or an equivalent combination of education and experience that demonstrates strong quantitative reasoning and analytical ability.
• Deep expertise in analytics and machine learning, with hands‑on experience across the full modeling lifecycle; experience in fraud and/or credit analytics preferred.
• Strong investigative analytics mindset – skilled at identifying patterns, forming hypotheses, and drawing meaningful conclusions from complex, large‑scale datasets.
• Demonstrated ability to lead, mentor, and develop data scientists.
• Experience working with clients or business partners in a consulting, advisory, or client‑facing analytics role.
• Able to translate an ambiguous client need into a well‑defined hypothesis with an analytical plan to address it.
• Experience designing scalable analytical processes, tools, or frameworks – ideally in a context where repeatability and efficiency were business priorities.
• Strong Python skills for data analysis and machine learning, including PySpark, Polars, Num Py, and Pandas; familiarity with large‑scale data processing frameworks and cloud platforms, especially Spark and AWS.
• Willingness to travel periodically for on‑site client…