Fraud Analytics Engineer

Short Summary

Fraud Analytics Engineer at Experian. About the employer 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…

Key Details

• Position / opportunity: Fraud Analytics Engineer
• Organization: Experian
• Country / coverage: United States
• Location: United States, UNITED STATES, United States
• Work arrangement: On-site
• Opportunity type: Jobs
• Sector: Information Technology
• Compensation: Not specified
• Application deadline: Deadline not specified

Description

About the employer

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

Responsibilities

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.

Responsibilities

• 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.
• 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

Requirements / Eligibility

• 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

Benefits / Compensation

• Flexible work environment, ability to work remote, hybrid or in-office
• Flexible time off including volunteer time off, vacation, sick and 12-paid holidays
• 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 To Apply

Apply to Experian for Fraud Analytics Engineer using the position-specific application form.