Analytics Engineer

Company Description

Experian is a global data and technology company dedicated to powering opportunities for individuals and businesses worldwide. We serve diverse markets, including financial services, healthcare, automotive, agribusiness, and insurance. Experian invests in its people and advanced technologies to harness the power of data, employing 25,200 individuals across 32 countries.

Job Description

The Fraud Analytics & Commercialization team is instrumental in driving Experian's fraud analytics business through four integrated functions: pre-sales engagement, scalable and custom solutions, consulting, and operational enablement. Our objective is to become the industry's preferred provider.

We are seeking an Analytics Engineer, Fraud Analytics Infrastructure, to join our Fraud Analytics team. The ideal candidate excels at the intersection of data engineering, infrastructure, and machine learning, with a strong focus on the reliability, scalability, and usability of the platforms their colleagues depend on. You will collaborate closely with data scientists, engineers, and product partners to build, maintain, and continuously enhance the analytics ecosystem that supports fraud attribute development, model building, and model deployment. This includes identifying opportunities to boost efficiency and stability throughout the entire modeling lifecycle. Key skills include navigating ambiguity, an impact-focused mindset, critical thinking, and a proactive approach to cross-team collaboration. You are curious about the latest tools and AI solutions, eager to evaluate their potential, and integrate the best ones into the team's workflows. Candidates who have demonstrated initiative and a capacity to learn and adapt without explicit guidance will find this role and team a strong fit.
You will report to the Data Modeling Director.

You'll have the opportunity to:

• Develop scalable Python-based data pipelines and backend services for analytics workflows.
• Design software systems utilizing object-oriented programming principles and robust engineering practices.
• Create and support platforms that facilitate 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 optimize 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 enhance platform efficiency and stability.

Qualifications

• 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 will be considered.
• Experience developing applications and data pipelines using Python, including proficiency with 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

• Generous compensation package and bonus plan.
• Core benefits including medical, dental, vision, and matching 401K.
• Flexible work environment with options for remote, hybrid, or in-office arrangements.
• Flexible time off, including volunteer time off, vacation, sick leave, and 12 paid holidays.
• Explore all our exciting benefits: https://myexperianbenefits.com/

Experian's unique, people-first, inclusive, and purpose-driven culture has earned multiple awards, including World's Best Workplaces™ 2025 (Fortune Global Top 25) and Great Place To Work™ certifications in 26 countries. Learn more about Experian Life on social media or explore our Careers Site.

Our compensation reflects the cost of labor across various U.S. geographic markets. The base pay range for this position is listed above. Individual pay within this range is determined by factors such as work location and job-related skills, experience, and education. You will also be eligible for variable pay opportunities.

Experian is an Equal Opportunity Employer, committed to protecting veterans and individuals with disabilities. If accommodation is needed, please inform us at the earliest opportunity.

#LI-Remote
This is a remote position.