Researcher, Feminist Philanthropy
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Women's Funding Network (WFN)
Remote (local)- Career category: Research/ Data analysis
- Job type: Job
- Humanitarian or Development: Development
- Experience level: 0-5 years
- Organisation type: Funds
- Remote option: Remote (local)
- Right to work requirements: Right to work required in advance
- Renumeration: $85,000-$105,000 / yearly
- Work schedule: Full-time
- Length of contract: Temporary/ Fixed-term
- Deadline: 27/10/2024
- Location: United States
ABOUT WFN
We believe that when philanthropy invests in women’s foundations and gender justice funders, we empower a deeply intersectional movement that fights for policies and standards across lines of race, class, and gender. WFN is the largest philanthropic alliance in the world dedicated to advancing the essential role of these funders in the unwavering fight for gender equality and justice.
RESPONSIBILITIES
• Work with a team to formulate and answer research questions about WFN and feminist philanthropy using quantitative and qualitative data from a variety of sources
• Identify and employ strategies to retrieve, analyze, and summarize quantitative data about nonprofit organizations and grantmaking.
• Use research results to write reports, fact sheets, blogs, and other knowledge resources to share learnings about the sector. • Interpret and explain complex data in a way that is accessible to a broad and varied audience.
• Administer WFN’s annual member survey and analyze the data.
• Conduct literature reviews.
• Collect, clean, and code qualitative and quantitative data.
• Respond to internal and external research requests.
• Work with the Communications team to develop content related to research projects, including social media and press releases.
• Occasionally, present research findings to internal or external audiences via webinars and at conferences.
SKILLS NEEDED TO BE SUCCESSFUL
• B.A./B.S. in a related field (e.g., economics, statistics, data science, public policy, philanthropy, nonprofit leadership) with minimum three years professional research experience. Advanced degree highly preferred. Equivalent experience will also be considered.
• Preference for working in a strongly collaborative, multi-disciplinary environment.
• Knowledge of research methods and principles of statistics.
• Experience with advanced statistical modeling and/or data science techniques (e.g., network analysis, latent class analysis, random forest).
• Demonstrated ability to conduct statistical analysis using Python or R.
• Aptitude and willingness to learn new applications as opportunity and need develops.
• Excellent written and verbal communication skills.
• Ability to explain research methods, results, and social impact to a mainstream audience. Primary author in published research and articles highly preferred.
• Knowledge of Office 365 applications; proficiency in Excel.
• Exceptional attention to detail, strong problem-solving ability and logical reasoning skills, and the ability to detect anomalies in data.
• Strong organizational and planning skills, with ability to juggle multiple projects with competing deadlines.
• Willingness to perform other duties and special projects as needed/requested.
• Sensitivity and respect for racial, gender, sexual orientation, and cultural differences.
We believe that when philanthropy invests in women’s foundations and gender justice funders, we empower a deeply intersectional movement that fights for policies and standards across lines of race, class, and gender. WFN is the largest philanthropic alliance in the world dedicated to advancing the essential role of these funders in the unwavering fight for gender equality and justice.
RESPONSIBILITIES
• Work with a team to formulate and answer research questions about WFN and feminist philanthropy using quantitative and qualitative data from a variety of sources
• Identify and employ strategies to retrieve, analyze, and summarize quantitative data about nonprofit organizations and grantmaking.
• Use research results to write reports, fact sheets, blogs, and other knowledge resources to share learnings about the sector. • Interpret and explain complex data in a way that is accessible to a broad and varied audience.
• Administer WFN’s annual member survey and analyze the data.
• Conduct literature reviews.
• Collect, clean, and code qualitative and quantitative data.
• Respond to internal and external research requests.
• Work with the Communications team to develop content related to research projects, including social media and press releases.
• Occasionally, present research findings to internal or external audiences via webinars and at conferences.
SKILLS NEEDED TO BE SUCCESSFUL
• B.A./B.S. in a related field (e.g., economics, statistics, data science, public policy, philanthropy, nonprofit leadership) with minimum three years professional research experience. Advanced degree highly preferred. Equivalent experience will also be considered.
• Preference for working in a strongly collaborative, multi-disciplinary environment.
• Knowledge of research methods and principles of statistics.
• Experience with advanced statistical modeling and/or data science techniques (e.g., network analysis, latent class analysis, random forest).
• Demonstrated ability to conduct statistical analysis using Python or R.
• Aptitude and willingness to learn new applications as opportunity and need develops.
• Excellent written and verbal communication skills.
• Ability to explain research methods, results, and social impact to a mainstream audience. Primary author in published research and articles highly preferred.
• Knowledge of Office 365 applications; proficiency in Excel.
• Exceptional attention to detail, strong problem-solving ability and logical reasoning skills, and the ability to detect anomalies in data.
• Strong organizational and planning skills, with ability to juggle multiple projects with competing deadlines.
• Willingness to perform other duties and special projects as needed/requested.
• Sensitivity and respect for racial, gender, sexual orientation, and cultural differences.
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