Experian

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Senior Data Scientist – Alternative Data, AFS Solutions

Data ScientistData ScientistFull TimeRemoteTeam 10,001+Since 1996H1B SponsorCompany SiteLinkedIn

Location

United States

Posted

17 days ago

Salary

$133.1K - $239.6K / year

Bachelor Degree7 yrs expEnglishNumpyPandasPythonSQL

Job Description

• 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.

Job Requirements

  • 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.

Benefits

  • 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

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