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:
• 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
• 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:
• 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