Senior Analyst

The Nature Conservancy

Senior Analyst developing advanced reporting and AI-enhanced solutions for fundraising strategies at The Nature Conservancy. Collaborating with teams to analyze data and guide decision-making.

Posted 7/14/2026full-timeRemote • Washington • 🇺🇸 United StatesSenior💰 $95,500 - $142,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in advanced reporting, analytics, and AI-enhanced solutions to drive fundraising strategies, with a strong focus on data manipulation, predictive modeling, and collaboration across teams.

Highest-signal resume keywords

SQLPredictive ModelingData WarehousingExcel MacrosAI Tools

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data AnalysisReport GenerationRelational Data ManipulationDonor ProfilingSegmentation AnalysisFile Health AnalysisStatistical Software (SAS, Python, R)Machine LearningNatural Language ProcessingDimensional Data Models

Soft Skills

CollaborationProblem SolvingCommunication

Tools & Technologies

Data Warehousing ToolsExcelMachine Learning PlatformsAutomation Frameworks

Industry Keywords

Fundraising StrategiesDirect Marketing ProgramsAccountingFinance

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Develop and implement advanced reporting, analytics, and AI‑enhanced solutions to guide fundraising strategies.
Collaborate closely with Membership Acquisition and Strategy teams to deliver data‑driven and machine‑assisted insights.
Assess complex situations, evaluate alternatives, and design and implement processes that improve program effectiveness.
Implement analytical solutions including file health analysis, predictive models, donor profiling, and segmentation analysis.
Analyze and report on key data to leadership, utilizing appropriate tools for projects.

Requirements

What you’ll need

Bachelor’s degree in quantitative field and 6 years related experience or equivalent combination.
Experience designing and generating reports, and analyzing and interpreting the data.
Experience working with teams across organization.
Experience with accounting, finance, and direct marketing programs.
Experience manipulating relational data.
Experience with SQL and data warehousing tools.
Experience with OLTP and dimensional data models.
Experience with Excel, including macros and pivot tables.
Experience with statistical software package (SAS, Python, R or similar) and building predictive models.
Experience incorporating AI tools, such as machine‑learning platforms, natural‑language processing tools, or automation frameworks into analytical workflows to improve efficiency, insight generation, and decision‑making.
Experience, coursework, or other training in principles, practices, and procedures of relevant field.

Benefits

Comp & perks

Health care benefits
Flexible spending accounts
401(k) plan with an 8% employer match
Parental leave
Accrued paid time off
Life insurance
Disability coverage
Employee assistance program
Other life and work well-being benefits