About this role
Job Description
We are seeking a Data Analyst who is passionate about utilizing data and analytics to help us deliver on our mission. We are looking for someone who will proactively drive improvements in performance across our businesses: campaign, major giving, estate giving, leadership giving, and prospect research. This role focuses on analyzing performance, creating reports, building predictive models, and delivering actionable insights that optimize our programs, deepen supporter engagement, and drive revenue.
Responsibilities
• Act as a bridge between the business and analytics team, focusing on aligning data insights with business questions and goals.
• Deliver regular performance reports with actionable recommendations to enhance supporter engagement, retention, acquisition, and lifetime value.
• Strengthen strategic fundraising by supporting the optimization of portfolios, measuring success rates, and identifying opportunities and gaps.
• Gather, clean and analyze data from internal databases, surveys and web analytics to uncover trends and actionable insights.
• Build and maintain predictive models to identify and prioritize prospects, forecast goal attainment, and guide resource allocation.
• Design, develop, and maintain dashboards and reports that are visually compelling, performant, and user‑friendly.
• Collaborate with cross‑functional teams (fundraising, marketing, and operations) to measure program effectiveness, including conducting A/B testing and summarizing key learnings with recommendations.
• Consolidate key business performance insights from prior years to guide future planning, partnering with relevant teams to gather and analyze data.
• Help define and refine KPIs, benchmarks, and measurement frameworks for organizational programs.
Qualifications
• A bachelor's or graduate degree in data science, mathematics, engineering, or related field – or equivalent experience.
• 3+ years experience in data analysis, reporting, market research, or a similar field.
• Proficiency in SQL and Python, with the ability to work with diverse datasets and apply analytic techniques (e.g., regression, clustering, time-series forecasting).
• Experience building dashboards using Power BI (or equivalent tool) and creating calculated fields and measures using DAX.
• Proven success in translating data insights into strategic recommen