Fraud Analytics Engineer

Posted 30 Minutes Ago
Be an Early Applicant
Hiring Remotely in United States
Remote or Hybrid
104K-180K Annually
Senior level
Big Data • Marketing Tech • Analytics
The Role
Build scalable Python backend services, data pipelines, and analytics platforms supporting fraud attribute development, machine learning model development, deployment, and monitoring. Design maintainable production systems, implement CI/CD and infrastructure as code, manage AWS and on-premises environments, improve reliability and security, troubleshoot pipelines, and process large datasets for analytics and visualization.
Summary Generated by Built In
Company 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.

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

Job Description

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 an Analytics Engineer that operates at the intersection of data engineering, infrastructure, and machine learning.

You'll help to develop the analytics ecosystem that enables fraud attribute development, model building, and model deployment . Examples include identifying opportunities to increase efficiency and stability across the full modeling lifecycle. This is an individual contributor position and you will report into the Analytics and Data Science Director.

What you'll do

  • Build scalable backend services and data pipelines in Python, transforming large datasets into clean, usable inputs for analytics workflows
  • Design and maintain systems using object-oriented programming principles, with a focus on readability, modularity, and long-term maintainability
  • Develop and operate platforms that support code execution, data workflows, and the end-to-end analytics modeling lifecycle
  • Implement CI/CD pipelines and manage infrastructure as code to promote automated, reliable deployments
  • Improve analytics environments across AWS and on-premises systems, applying security and encryption best practices throughout
  • Monitor, troubleshoot, and resolve data pipeline issues; guide ongoing improvements to system reliability and performance
  • Support model development environments by ensuring feature engineering, model training, evaluation, and deployment workflows
  • Handle large-scale data ingestion, transformation, and aggregation, and create data visualizations and summaries that communicate findings
  • Help evaluate and incorporate innovations that can enhance the team's capabilities

Qualifications

  • 5+ years of experience in data science, analytics, or a related field
  • Bachelor's degree in Statistics, Applied Mathematics, Econometrics, or another quantitative discipline — or an equivalent combination of education and experience
  • Proficiency in Python—including PySpark, Polars, NumPy, and Pandas—with familiarity in Java
  • Experience with data structures, object-oriented programming, and system design principles
  • Hands-on experience building and maintaining production systems and data pipelines
  • Practical experience with AWS services (e.g., EC2, EMR, Airflow) and cloud security practices
  • Working knowledge of machine learning workflows and analytics model development
  • Experience with CI/CD pipelines, automated deployments, and Infrastructure as Code
  • Familiarity with containerization and orchestration tools
  • Proficiency in UNIX/Linux environments and scripting (e.g., Bash)
  • #LI-hybrid

Additional Information

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.

Skills Required

  • 5+ years of experience in data science, analytics, or a related field
  • Bachelor’s degree in Statistics, Applied Mathematics, Econometrics, another quantitative discipline, or equivalent education and experience
  • Proficiency in Python, including PySpark, Polars, NumPy, and Pandas
  • Familiarity with Java
  • Experience with data structures, object-oriented programming, and system design principles
  • Hands-on experience building and maintaining production systems and data pipelines
  • Practical experience with AWS services such as EC2, EMR, and Airflow
  • Knowledge of cloud security practices
  • Working knowledge of machine learning workflows and analytics model development
  • Experience with CI/CD pipelines and automated deployments
  • Experience with Infrastructure as Code
  • Familiarity with containerization and orchestration tools
  • Proficiency in UNIX/Linux environments and Bash scripting

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

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The Company
HQ: Dublin
16,292 Employees
Year Founded: 1980

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.

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