Experian Logo

Experian

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

Reposted 2 Days Ago
Remote
Hiring Remotely in United States
Senior level
Remote
Hiring Remotely in United States
Senior level
The Senior Data Scientist will develop custom analytics and ML models for AFS, focusing on non-prime lending, and work closely with clients to implement effective credit strategies.
The summary above was generated by AI
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).
  • Conduct segmentation, lift analysis, and champion/challenger testing to assess performance and incremental value.
  • Develop custom scorecards, policy rules, and ML models aligned with each client's risk appetite and regulatory requirements.
  • 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.
  • Contribute to AFS best practices, reusable frameworks, and internal accelerators for non‑prime analytics.

Qualifications

  • 5+ 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

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, collaboration, wellness, reward & recognition, volunteering... the list goes on. Experian's people first approach is award-winning; World's Best Workplaces™ 2024 (Fortune Top 25), Great Place To Work™ in 24 countries, and Glassdoor Best Places to Work 2024 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, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

Top Skills

Lightgbm
Numpy
Pandas
Python
Scikit-Learn
SQL
Xgboost
HQ

Experian Costa Mesa, California, USA Office

475 Anton Blvd, Costa Mesa, CA, United States, 92626

Experian Costa Mesa, California, USA Office

475 Anton Blvd, Costa Mesa, CA , United States, 92626

Similar Jobs

22 Hours Ago
In-Office or Remote
8 Locations
168K-297K Annually
Senior level
168K-297K Annually
Senior level
Blockchain • eCommerce • Fintech • Payments • Software • Financial Services • Cryptocurrency
As a Senior Data Scientist, you'll analyze large datasets, develop models, improve underwriting processes, and collaborate across teams to drive impactful credit strategies.
Top Skills: Data Visualization Tools (E.G. ModeLooker)PythonSQL
13 Minutes Ago
In-Office or Remote
Eden Prairie, MN, USA
92K-164K Annually
Senior level
92K-164K Annually
Senior level
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
As a Senior Actuarial Consultant, you will advance healthcare analytics, develop trend forecast models, and provide actionable insights for Medicare Advantage. Responsibilities include data analysis, model maintenance, and mentoring junior staff.
Top Skills: ExcelPythonRSASSQL
13 Minutes Ago
In-Office or Remote
Minnetonka, MN, USA
73K-130K Annually
Senior level
73K-130K Annually
Senior level
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Design, develop, test, and support applications in production, primarily focusing on API development, CI/CD pipeline management, and monitoring performance.
Top Skills: Ci/CdDynatraceGithub ActionsGrafanaJavaJfrog ArtifactoryKafkaKubernetesMavenMicroservicesMicrosoft Graph ApiMySQLPower AutomatePythonRest ApisSplunkXMLZabbix

What you need to know about the Los Angeles Tech Scene

Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.

Key Facts About Los Angeles Tech

  • Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
  • Key Industries: Artificial intelligence, adtech, media, software, game development
  • Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
  • Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account