Senior Data Scientist – Alternative Data, AFS Solutions

Experian

full-time

Posted on:

Location Type: Remote

Location: Remote • 🇺🇸 United States

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Salary

💰 $133,109 - $239,596 per year

Job Level

Senior

Tech Stack

NumpyPandasPythonSQL

About the role

  • 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.

Requirements

  • 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.
Benefits
  • Flexible Time Off: 20 Days

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
credit risk analyticsdata scienceadvanced analyticsmodelingfeature engineeringPythonSQLmodel evaluationmachine learningdata integration
Soft skills
client deliverycommunicationpresentationcollaborationproblem-solvingmentoringstrategic thinkinganalytical thinkingdocumentationinsight delivery