Principal Consultant – Analytics, Credit Strategy

Experian

full-time

Posted on:

Location Type: Remote

Location: Remote • 🇺🇸 United States

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Salary

💰 $176,036 - $316,865 per year

Job Level

Lead

Tech Stack

NumpyPandasPythonSQLTableau

About the role

  • Be the day‑to‑day analytics partner for clients on credit strategy, risk optimization, and portfolio performance.
  • Translate client goals into clear analytical questions, project plans, and structured workflows.
  • Use Python and SQL to explore data, validate hypotheses, and support analytical workflows developed by Data Science teams.
  • Contribute to the development of credit strategies, policy rules, and models across underwriting, account management, pricing, and collections.
  • Conduct segmentation and performance deep dives to identify applicable client opportunities.
  • Interpret model outputs and analytical findings, turning them into clear recommendations aligned with client goals and constraints.
  • Produce client‑ready deliverables, including presentations, dashboards, summaries, and executive readouts.
  • Present insights to client partners, including risk, analytics, and business leaders.
  • Support Sales and Account teams with pre‑sales analytics, POVs, and proposal inputs.
  • Work with our teams (Data Science, Product, Engineering) to ensure client requirements are understood and delivered.
  • Support post‑implementation work such as monitoring, performance tracking, and strategy optimization.
  • Ensure analytical work follows data quality, governance, and regulatory expectations.

Requirements

  • 3–6 years of experience in analytics, consulting, credit risk, or financial services.
  • Proficiency in Python (Pandas, NumPy, basic modeling/visualization) for analysis.
  • SQL skills for querying, validating, and analyzing large datasets.
  • Familiarity with credit risk, portfolio analytics, and the credit lifecycle.
  • Experienced working with scores, attributes, segments, and performance metrics.
  • Convert analytical results into clear, business‑focused recommendations.
  • Experienced working directly with clients or partners in consulting or professional services.
  • Experienced in credit risk, FinTech, or decisioning platforms.
  • Familiarity with model performance metrics (AUC, KS, lift, stability, and bad‑rate curves).
  • Experienced supporting machine learning or scorecard‑based model development.
  • Exposure to visualization tools (Tableau, Power BI, Looker).
  • Experienced supporting pre‑sales, pilots, or proof‑of‑value engagements.
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
PythonSQLdata analysismodelingvisualizationcredit riskportfolio analyticsperformance metricsmachine learningscorecard development
Soft skills
client communicationanalytical thinkingproject managementpresentation skillsrecommendation developmentcollaborationproblem-solvingconsultingbusiness acumenstrategic thinking