Lead Revenue Intelligence Quant Analyst

Acrisure; Austin (TX); On-site; USD 137,000 - 185,000; Full time

Benefits offered by this job

Medical, dental, vision

401(k) and retirement benefits

Paid time off

Job summary

Acrisure seeks a Lead Quantitative Analyst in Revenue Intelligence to architect econometric models connecting policy and commission data to GAAP results. You’ll build transparent, driver-based models and production-ready tools to inform strategic decisions.

The role emphasizes interpretable analyses, collaboration with FP&A, and on-site collaboration while leveraging Python, SQL, and Palantir in a fintech insurance context.

Qualifications

• Bachelor's degree in quantitative field (Finance/Economics/Statistics/Math) required or equivalent.
• 5–10 years in quantitative modeling or economic research with business application.
• Strong Python and SQL for data manipulation and automation.
• Proficiency in Power BI or similar BI tools for dashboards.
• Experience with Palantir or similar enterprise data platforms a plus.

Responsibilities

• Develop time-series and econometric models linking operational data to GAAP revenue.
• Quantify drivers of revenue across segments, channels, and geography; ensure interpretability.
• Build scenario analysis tools for real-time forecasting for planning cycles.
• Create data-driven visualizations and dashboards for senior leadership.

Skills

Econometric modeling

Time-series analysis

Regression analysis

Causal inference

Financial analysis

Python

SQL

Power BI

Palantir

Claude Code

Education

Bachelor's degree in quantitative field

Master's degree preferred

Tools

Palantir

Python

SQL

Power BI

Job description

Acrisure seeks a Lead Quantitative Analyst in Revenue Intelligence to architect econometric models connecting policy and commission data to GAAP results. You’ll build transparent, driver-based models and production-ready tools to inform strategic decisions.

The role emphasizes interpretable analyses, collaboration with FP&A, and on-site collaboration while leveraging Python, SQL, and Palantir in a fintech insurance context.