Data Engineering Analyst Lead/Scientist
- United States
- Analytics
- Permanent
- Home
- Full Time
- $115,747 - $208,344
We are looking for an experienced Data Engineering Analyst Lead/Scientist to join our Data Intelligence & Attributes team to transform raw trade and transaction-level data into high-value consumer features that guide decisions across the credit lifecycle from marketing and acquisition to account management and collections. This is a fully remote position. You will report to the Director of Data Engineering.
You'll have opportunity to:
- Engineer and validate consumer-level attributes from credit bureau and alternative data sources.
- Apply statistical techniques to uncover insights and improve predictiveness.
- Monitor attribute performance for stability, compliance, and accuracy.
- Build dashboards and visualizations (Tableau) to communicate findings.
- Collaborate with engineering to productionalize prototypes into scalable solutions.
- Partner with product, risk, and business teams to maximize impact across marketing, risk assessment, and collections.
- Engage with clients to explain analytics and translate technical results into applicable business insights.
Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realize their financial goals and help them save time and money.
We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments.
We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com.
- Master's degree in a quantitative field (Statistics, Data Science, Economics, Computer Science).
- 5+ years in data science or advanced analytics within credit or financial services.
- Strong Python and SQL skills; experience with Tableau or similar BI tools.
- Experience with credit bureau and alternative data.
- Experience designing and deploying consumer attributes for production.
Preferred:
- Client-facing experience in analytics or credit risk.
- Familiarity with AWS or other cloud platforms.
- Knowledge of regulatory compliance and data privacy in credit contexts.
At Experian, our people and culture set us apart. We're deeply committed to creating an environment where everyone feels they belong and can excel. From inclusion and authenticity to work/life balance, development, wellness, collaboration, and recognition, we focus on what truly matters. Our people-first approach has earned us global recognition: World's Best Workplaces™ 2024 (Fortune Top 25), Great Place To Work™ 2025 in 26 countries, and Glassdoor Best Places to Work 2024, among others.
Want to see what life at Experian is really like? Explore Experian Life on social or visit our Careers Site.
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.
Explore Experian's award winning 'people first' culture.
Being part of Experian is exciting. Every day brings new challenges, new opportunities, new ways for us to do what we do best: using our innovative technologies and data to work in new and surprising ways. All brought together in a single thought: Discover the Unexpected.
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