Experian

Compensation

Full Description

Job Description: • Manage our thought leadership 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. • Leverage aggregated and anonymized datasets to produce market-level insights while maintaining compliance. • Collaborate with Data Science teams to validate assumptions, interpret model behavior, and ensure analytical rigor in published insights. • Work with Product to translate platform capabilities and analytical innovation into clear, market-relevant messaging. • Identify new industry trends using both qualitative indicators and quantitative evidence. • Represent us externally, presenting analytically grounded insights to senior client and industry audiences. • Establish standards and review processes to ensure quality, defensibility, and consistency across all thought leadership outputs. Requirements: • 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. • Experience converting technical analysis into clear insights for executive and non-technical audiences. • Experience supporting or influencing enterprise-level sales efforts using analytical insight. • Experience in leadership, market analytics enablement roles. • Familiarity with machine learning concepts and their application in decisioning systems. • 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. • Experience speaking at conferences or industry forums. Benefits: • Flexible Time Off: 20 Days