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Data Engineering Analyst Lead/Scientist

Experian
8 hours ago
Full-time
Remote
United States
Automation

Company Description

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 work towards 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.

Job Description

Experian is looking for an experienced Data Engineering Analyst Lead/Scientist to join our Data Intelligence & Attributes team. This team transforms raw trade and transaction-level data into high-value consumer features. These features 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 will:

  • 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.

Qualifications

  • 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.
  • 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.
  • 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.

Additional Information

Benefits/Perks:

  • Great compensation package and bonus plan
  • Core benefits including full medical, dental, vision, and matching 401K
  • Flexible schedule, ability to work remotely, hybrid, or in-office
  • Flexible time off, including volunteer time off, vacation, sick, and 12-paid holidays

Additional Information

Our uniqueness is that we celebrate yours. Experian's culture and people are important differentiators. We take our people agenda very seriously and focus on what matters; DEI, work/life balance, development, authenticity, engagement, collaboration, wellness, reward and recognition, volunteering... the list goes on. Experian's people first approach is award-winning; Great Place To Workβ„’ in 24 countries, FORTUNE Best Companies to work and Glassdoor Best Places to Work (globally 4.4 Stars) to name a few. Check out Experian Life on social or our Careers Site to understand why.

Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is an important part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, color, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

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