Fraud Analytics Engineer

Experian; United States; Hybrid; USD 104,000 - 180,000; Full time

Benefits offered by this job

Great compensation package and bonus

Medical, dental, vision, 401K matching

Flexible work environment - remote, hy

Flexible time off

Job summary

Experian is seeking an Analytics Engineer who operates at the intersection of data engineering, infrastructure, and machine learning. The role focuses on developing analytics ecosystems for fraud attribute development, model building, and deployment, reporting to the Analytics and Data Science Director.

You will build scalable data pipelines, improve end-to-end modeling lifecycles, and implement CI/CD with infrastructure as code across AWS and on-prem environments.

Qualifications

• Bachelor's degree in Statistics, Applied Mathematics, Econometrics, or another quantitative discipline or equivalent experience.
• 5+ years of experience in data science, analytics, or related field.
• Proficiency in Python including PySpark, Polars, NumPy, and Pandas; familiarity with Java.
• Hands-on experience building and maintaining production systems and data pipelines.
• Experience with AWS services like EC2, EMR, and security practices.
• Knowledge of ML workflows and analytics model development.
• Experience with CI/CD pipelines and Infrastructure as Code.
• Familiarity with containerization and orchestration tools.

Responsibilities

• Build scalable backend services and data pipelines in Python for analytics workflows.
• Design and maintain systems using OO principles for readability and maintainability.
• Develop and operate platforms that support code execution, data workflows, and end-to-end modeling lifecycle.
• Implement CI/CD pipelines and manage infrastructure as code for automated deployments.
• Improve analytics environments across AWS and on-premises with security best practices.
• Monitor and troubleshoot data pipelines; drive reliability improvements.
• Support model development environments including feature engineering and deployment workflows.
• Handle large-scale data ingestion, transformation, and aggregation; create data visualizations.

Skills

Python

AWS

CI/CD

UNIX/Linux

Bash

Education

Bachelor's in Statistics/Applied Math or related

Tools

PySpark

Polars

NumPy

Pandas

Java

Airflow

AWS EC2/EMR

Job description

• Job Posting - Salary Range: $103,669 - $179,693
• Department: Analytics
• Flexible Time Off: 20 Days
• Schedule: Full Time
• Shift: Day Shift
• Compensation: USD 103,669 - USD 179,693 - yearly

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:

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

• 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

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.