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Experian

Senior Data Scientist - Alternative Data & AFS Solutions (Non-Prime Lending)

Posted 19 Days Ago
Remote
Hiring Remotely in United States
Senior level
Remote
Hiring Remotely in United States
Senior level
Lead custom analytics and ML model development for non-prime lending using traditional and alternative data. Scope and deliver credit strategies (underwriting, pricing, collections), engineer features, evaluate data sources, present insights to clients, and support model implementation, monitoring, and optimization.
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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 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.

Job Description

We are looking for an experienced Senior Data Scientist to join our Alternative Financial Services (AFS) department, supporting clients in the non‑prime and near‑prime lending markets. You'll design custom analytics, credit strategies, and machine‑learning models using both traditional and alternative data. This is a client‑facing, solution‑oriented role requiring technical depth and the ability to convert complex analyses into practical, applicable recommendations. You will report to the VP of Analytics Product Build, Innovation, and Scores.

You'll have opportunity to:

  • Lead custom analytics and modeling engagements from scoping through delivery and ongoing support.
  • Develop credit strategies and ML models (underwriting, line assignment, pricing, early warning, collections).
  • Engineer features from alternative, transactional, and bureau data (e.g., recency, frequency, volatility, trend, and behavioral metrics).
  • Evaluate and integrate third‑party/alternative data sources (sub‑prime bureaus, cash-flow, telco, utility, and specialty data).
  • Partner with clients to build end‑to‑end credit strategies that balance approvals, losses, efficiency, and customer experience.
  • Deliver clear, executive‑ready insights, documentation, and strategy recommendations.
  • Present results directly to risk leaders, analytics teams, and senior client partners.
  • Support model implementation, monitoring, stability analysis, and ongoing optimization.
  • Work cross‑functionally with Product, Engineering, and Sales to align custom solutions with broader AFS capabilities.

Qualifications

  • 7+ years in credit risk analytics, data science, or advanced analytics, with experience in non‑prime or near‑prime lending.
  • Hands‑on modeling experience using alternative data.
  • Proficiency in Python (Pandas, NumPy, scikit‑learn, XGBoost/LightGBM) for feature engineering, modeling, and analysis.
  • Advanced SQL experience working with complex, and imperfect datasets.
  • Experience with non‑prime risk dynamics: thin‑file consumers, volatility, fraud risk, early‑default behavior.
  • Experience with model evaluation (AUC, KS, lift, bad‑rate curves, stability, PSI).
  • Work directly with clients and translate analytics into deployable strategies.
  • Explain complex models in clear business terms.
  • Background in financial services, alternative lending, FinTech, or specialty finance.
  • Experience with AFS data sources (Clarity, FactorTrust, MicroBilt, cash‑flow or specialty bureaus).
  • Familiarity with model governance, explainability, and regulatory considerations in non‑prime lending.
  • Experience deploying or supporting ML models in production environments.
  • Exposure to fraud, identity, or first‑payment‑default (FPD) modeling.
  • Experience mentoring junior data scientists or analysts.
  • Consult, client delivery, or solution‑oriented project experience.

Additional Information

Benefits/Perks:

  • Great compensation package
  • 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

 

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. This position is also 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.

Top Skills

Clarity
Factortrust
Lightgbm
Microbilt
Numpy
Pandas
Python
Scikit-Learn
SQL
Xgboost

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