Senior Revenue Analytics & Forecasting Lead

Acrisure, LLC; Grand Rapids (MI); Hybrid; USD 137,000 - 185,000; Full time

Benefits offered by this job

Health insurance

401(k) plan

Paid time off

Job summary

Acrisure is seeking a Lead Quantitative Analyst to advance revenue intelligence by building production‑quality models that connect insurance operations to GAAP results. You will craft time‑series forecasts and driver‑based econometric analyses for senior leadership, using Python, SQL, and Palantir in a scalable analytics environment.

The role emphasizes transparent, explainable models over black‑box predictions, with collaboration across FP&A, Strategic Finance, and Data & Analytics teams.

Qualifications

• Bachelor's degree in Quantitative Finance, Economics, Statistics, Mathematics, or a closely related quantitative field; Master's preferred.
• 5–10 years of experience in quantitative modeling, financial analysis, or economic research.
• Deep expertise in econometric and statistical modeling methods with interpretable driver-based approaches.
• Experience connecting operational drivers to financial results in financial services or insurance contexts.
• Proficiency in Python and SQL for data manipulation and model development.

Responsibilities

• Build and maintain time-series forecasting models for GAAP revenue with drivers like retention, new business, and pricing trends.
• Develop econometric models to quantify drivers of revenue across client segments and channels.
• Design scenario analysis tools for real-time revenue forecasting under varying assumptions.
• Connect policy-level and transaction-level data to GAAP results to bridge production metrics with revenue.

Skills

Econometric modeling

Time-series analysis

Python

SQL

Power BI

Palantir

Causal inference

Communication

Education

Bachelor's degree in Quantitative field

Master's degree preferred

Tools

Python

SQL

Palantir

Power BI

Job description

Acrisure is seeking a Lead Quantitative Analyst to advance revenue intelligence by building production‑quality models that connect insurance operations to GAAP results. You will craft time‑series forecasts and driver‑based econometric analyses for senior leadership, using Python, SQL, and Palantir in a scalable analytics environment.

The role emphasizes transparent, explainable models over black‑box predictions, with collaboration across FP&A, Strategic Finance, and Data & Analytics teams.