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.
Job DescriptionThe 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.
We're looking for an Analytics Engineer, Fraud Analytics Infrastructure, to join our Fraud Analytics team. As the ideal candidate, you thrive at the intersection of data engineering, infrastructure, and machine learning, and care about the reliability, scalability, and usability of the platforms your colleagues depend on. You'll work closely with data scientists, engineers, and product partners to build, maintain, and continuously improve the analytics ecosystem that enables fraud attribute development, model building, and model deployment, including identifying opportunities to increase efficiency and stability across the full modeling lifecycle. Core skills include navigating ambiguity, an impact-focused mindset, critical thinking, and an eagerness to collaborate across teams. You are curious about the latest tools and AI solutions, will evaluate their potential, and help bring the best of them into the team's workflows. Candidates who have taken an unconventional path and demonstrated the curiosity to figure things out without a blueprint will find this role and team to be a good fit.
You will report to the Data Modeling Director.
You'll have the opportunity to:
- Build scalable Python-based data pipelines and backend services for analytics workflows.
- Design software systems using object-oriented programming and sound engineering practices.
- Create and support platforms that allow analytics development, model training, and model deployment.
- Implement and maintain CI/CD pipelines and infrastructure-as-code solutions for automated deployments.
- Manage cloud and on-premises analytics environments, including AWS infrastructure and security controls.
- Monitor, troubleshoot, and improve data pipelines, platform performance, and system reliability.
- Support machine learning and fraud modeling workflows, including feature engineering and model deployment.
- Implement new technologies, including AI-based solutions, to improve platform efficiency and stability.
- 3+ years of experience in data science, analytics, data engineering, or a related field.
- Bachelor's or advanced degree in Statistics, Applied Mathematics, Econometrics, or another quantitative field; equivalent experience considered.
- Experience developing applications and data pipelines using Python, including PySpark, Polars, NumPy, and Pandas.
- Familiarity with Java and object-oriented programming concepts.
- Experience building, deploying, and supporting production systems and data platforms.
- Experience with AWS services such as EC2, EMR, and Airflow, including cloud security best practices.
- Experience with machine learning workflows and analytics model development environments.
- Experience with CI/CD processes, Infrastructure as Code, containerization tools, and UNIX/Linux environments.
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://myexperianbenefits.com/.
Our uniqueness is that we celebrate yours. Experian's people first, inclusive and purpose driven culture is multi award-winning; World's Best Workplaces™ 2025 (Fortune Global Top 25), Great Place To Work™ in 26 countries to name a few. Check out Experian Life on social or explore our Careers Site to understand why.
Our compensation reflects the cost of labor across several U.S. geographic markets. The base pay range for this position is listed above. Within this range, individual pay is determined by work location and additional factors such as job-related skills, experience, and education. You will be also eligible for a variable pay opportunity.
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.
#LI-Remote
This is a remote position.
Skills Required
- 3+ years of experience in data science, analytics, data engineering, or related field
- Bachelor's or advanced degree in Statistics, Applied Mathematics, Econometrics, or quantitative field (or equivalent experience)
- Experience developing applications and data pipelines using Python (including PySpark, Polars, NumPy, Pandas)
- Familiarity with Java and object-oriented programming concepts
- Experience building, deploying, and supporting production systems and data platforms
- Experience with AWS services such as EC2, EMR, and Airflow, including cloud security best practices
- Experience with machine learning workflows and analytics model development environments
- Experience with CI/CD processes, Infrastructure as Code, containerization tools, and UNIX/Linux environments
Experian Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Experian and has not been reviewed or approved by Experian.
-
Healthcare Strength — Medical and dental coverage is described as strong, with expanded mental health resources and telemedicine options. Coverage includes inclusive services such as gender transition and fertility support.
-
Leave & Time Off Breadth — Time-off offerings are generous, including substantial PTO/vacation, paid holidays, and paid volunteer days with options to purchase additional leave. Parental leave is available for birth and non-birth parents alongside flexible working arrangements that support work-life balance.
-
Retirement Support — Retirement programs include a 401(k) with company matching and contributory pension schemes in some regions. These elements complement base pay and bonuses to form a competitive total rewards package.
Experian Insights
What We Do
Experian unlocks the power of data to create opportunities for consumers, businesses and society. During life’s big moments – from buying a home or car, to sending a child to college, to growing a business exponentially by connecting it with new customers – we empower consumers and our clients to manage data with confidence so they can maximize every opportunity. We gather, analyse and process data in ways others can’t. We help individuals take financial control and access financial services, businesses make smarter decision and thrive, lenders lend more responsibly, and organizations prevent identity fraud and crime. For more than 125 years, we’ve helped consumers and clients prosper, and economies and communities flourish – and we’re not done. Our 20,600 people in 43 countries believe the possibilities for you, and our world, are growing. We’re investing in new technologies, talented people and innovation so we can help create a better tomorrow. About Experian: Bringing data to life requires creativity, passion, flexibility and expertise. We want you to share in our success. That's why we offer rewards that recognise great performance. Working in a culture of collaboration, achievement and respect we will give you the support and encouragement you need to develop your skills and talents and progress your career. Everyday our people bring enthusiasm, innovation and inspiration to work and if this sounds like you connect with us at Experian.
