Principal Consultant – Analytics, Credit Strategy

Job Description: • 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 Apply tot his job