Impact Modeling Analyst - Remote ROI Forecasting

Rosepat Opportunity Manager; Northern (KY); Hybrid; USD 90,000 - 115,000; Full time

Benefits offered by this job

Health insurance

401(K) plan

Unlimited vacation

Remote-friendly

Job summary

GitLab Foundation is a fully remote organization based in the United States, focused on maximizing lifetime earnings through education, training, and strategic philanthropy. The Impact Modeling Analyst will build and maintain ROI and impact forecasting models to guide grantmaking decisions, portfolio strategy, and advisory engagements.

The role emphasizes rigorous quantitative analysis, collaboration with grantees, and the use of emerging AI and data science techniques to improve measurement of

Qualifications

• 5+ years of experience in economic modeling, impact analysis, or a related analytical role.
• Strong quantitative and analytical skills, including statistics and econometrics.
• Proficiency with data visualization tools and spreadsheets.
• Ability to translate complex analyses for technical and non-technical audiences.

Responsibilities

• Develop and maintain impact and ROI models for grantmaking and advisory engagements.
• Analyze data from grantees, research, and partners to improve model inputs and outputs.
• Create clear visualizations and reports for internal and external audiences.
• Document modeling processes and maintain datasets for reproducibility.
• Explore AI-enabled tools and emerging methods to strengthen modeling capabilities.

Skills

Quantitative analysis

Data visualization

Econometrics

Excel/Google Sheets

English communication

Tools

Tableau

R

Python

Job description

GitLab Foundation is a fully remote organization based in the United States, focused on maximizing lifetime earnings through education, training, and strategic philanthropy. The Impact Modeling Analyst will build and maintain ROI and impact forecasting models to guide grantmaking decisions, portfolio strategy, and advisory engagements.

The role emphasizes rigorous quantitative analysis, collaboration with grantees, and the use of emerging AI and data science techniques to improve measurement of