Experian-posted about 5 hours ago
Full-time • Mid Level
Remote • Madison, MS
5,001-10,000 employees

We are looking for a Principal Consultant to deliver client‑facing analytics and credit strategy engagements across the credit lifecycle. You will work directly with clients to solve complex business problems using data, analytics, and modeling insights, translating technical work into practical, deployable strategies. You will be collaborative, partnering with Data Science, Product, and Sales to guide measurable outcomes. You will report to the VP of Analytics Product Build, Innovation, and Scores. You will be fully remote. You'll have opportunity to: 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.

  • 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.
  • 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.
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