Senior Manager, Thought Leadership and Insights

Job Description

We are looking for a credible Senior Manager to lead our team. You will transform advanced analytics, internal data assets, and market intelligence into compelling narratives. These narratives are data-backed and support strategic sales plans, influence industry conversations, and position us as a leader in data-driven decisioning. You will work across Analytics, Product, Sales, and Marketing. You will report to the VP of Analytics Product Build, Innovation, and Scores. You will be fully remote.

• You will manage our strategy, grounded in data analysis and empirical thoughtfulness.
• Use Python and SQL to independently explore datasets, validate hypotheses, and surface unique insights.
• Translate analytical findings, model outputs, and product capabilities into clear, market‑facing narratives that demonstrate value.
• Develop industry perspectives on credit lifecycle optimization, alternative data, machine learning adoption, portfolio risk, fraud, and regulatory trends.
• Support large strategic sales opportunities with analytical framing, benchmarks, and data‑driven proof points that strengthen value propositions.
• Create executive‑ready content—including industry reports, white papers, sales enablement decks, client POVs, and conference presentations.
• Collaborate with Data Science teams to validate assumptions, interpret model behavior, and ensure analytical rigor in published insights.
• Identify new industry trends using both qualitative indicators and quantitative evidence.
• Represent us externally, presenting Experience researching and generating leads grounded insights to senior client and industry audiences.

Qualifications

• 8+ years of experience in data science, analytics, credit risk, product strategy, or financial services consulting.
• Proficiency in Python (Pandas, NumPy, SciPy, and visualization libraries) for exploratory analysis generation.
• Advanced SQL skills for querying large datasets and validating metrics across complex data sources.
• Experience with data‑driven decisioning, analytics, and the credit lifecycle.
• Experience interpreting model performance metrics (AUC, KS, lift, stability) and translating them into business possible effects.
• Understanding of regulatory and compliance considerations related to data usage and analytics.
• Experience with large‑scale data platforms, credit attributes, scores, or decision engines.
• Background in client‑facing consulting, pre‑sales analytics, or strategy roles.