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Senior Analyst, Fundraising Data & Analytics

Posted about 2 months agoViewed

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💎 Seniority level: Senior

📍 Location: Australia, Austria, Bangladesh, Belgium, Brazil, Canada, Colombia, Costa Rica, Croatia, Czech Republic, Denmark, Egypt, Estonia, Finland, France, Germany, Ghana, Greece, India, Indonesia, Ireland, Israel, Italy, Kenya, Mexico, Netherlands, Nigeria, Peru, Poland, Singapore, South Africa, Spain, Sweden, Switzerland, Uganda, United Arab Emirates, United Kingdom, United States of America, Uruguay

💸 Salary: 102437 - 161869 USD per year

🔍 Industry: Non-profit, Education

🏢 Company: Wikimedia Foundation👥 251-500💰 $2,100,000 Grant about 5 years ago

🗣️ Languages: English

🪄 Skills: PythonSQLBusiness IntelligenceETLGitNosqlCommunication SkillsCollaborationWritten communicationTroubleshooting

Requirements:
  • Highly proficient in SQL for data transformation and queries.
  • Skilled in developing impactful data visualizations in a business intelligence platform.
  • Practical statistical expertise and understanding of digital campaigns.
  • Comfortable with data-related Python and/or R packages for ad hoc analysis.
  • Experience using predictive modeling to answer actionable business questions.
  • Comfortable with giving and receiving code reviews through git.
  • Ability to document work for benefit of teammates and stakeholders.
  • Experience troubleshooting SQL queries and pipelines.
  • Accurate work estimation and timely surfacing of obstacles.
  • Growth mindset and willingness to experiment with new tools.
  • Excellent verbal and written communication skills.
Responsibilities:
  • Delivering actionable insights and analysis on global fundraising campaigns and strategic objectives.
  • Developing and tracking key performance indicators across different channels in collaboration with fundraising leadership.
  • Partnering with colleagues in fundraising and finance to create multi-year revenue forecasting.
  • Conducting statistical analysis and providing guidance on A/B testing setup.
  • Transforming and cleaning data to support analytics needs.
  • Peer reviewing teammates' work to ensure data quality.
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