Data Engineering Analyst Lead/Scientist

Experian

4h • Remote

About The Position

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. 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.

Requirements

• 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.

Nice To Haves

• 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.

Responsibilities

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 501-1,000 employees