Senior Manager, Thought Leadership and Industry Insights

Company Description

Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to realize their financial goals and help them save time and money.

We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments.

We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at

We are looking for a credible Senior Manager to lead our thought leadership and industry insights agenda. This role transforms advanced analytics, internal data assets, and market intelligence into compelling, data-backed narratives that support strategic sales initiatives, influence industry conversations, and position the company as a leader in data‑driven decisioning. Success requires deep analytical fluency in Python and SQL, paired with executive storytelling.

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’ll have opportunity to:

• 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.

• 8+ years of experience in data science, analytics, credit risk, product strategy, or financial services consulting.
• Proficiency in Python (Pandas, Num Py, Sci Py, 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…