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Senior Analyst, Fundraising Data & Analytics (Contract)CiviCRM • United States
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Senior Analyst, Fundraising Data & Analytics (Contract)

CiviCRM
  • US
    United States
  • US
    United States
Postuler Maintenant

À propos

SENIOR ANALYST, FUNDRAISING DATA & ANALYTICS (CONTRACT)
Duration: One-year contract Location: Remote, Preferred that the candidate be based between UTC−05:00 and UTC+00:00
Summary
The Wikimedia Foundation is the non‑profit organization that operates Wikipedia—one of the most popular websites in the world, serving nearly half a billion users every month. The Foundation is the only non‑profit among the top 50 websites, and is supported by a community of millions of individual donors. Join the Wikimedia Foundation in our ambitious project to empower people to create and share the sum of all human knowledge.
The fundraising team at the Wikimedia Foundation conducts worldwide campaigns across nearly 40 countries and 20 languages, collecting donations to support the Wikimedia Foundation’s mission to empower and engage people around the world with free knowledge. The Fundraising Operations team has an opening for a senior data analyst on our team, to support data‑driven decisions to improve the effectiveness of our fundraising strategies, while staying true to our values of openness, transparency, and respect of user privacy. This role will be a full‑time (40 hours/week) contractor position.
As a Senior Data Analyst, you’ll be part of a small and collaborative analytics team with an analytics engineer and two fellow analysts, supported by the Senior Manager, Fundraising Data & Analytics as well as a data engineer on the adjacent fundraising technology team. This team supports our fundraising teams, from online fundraising to donor relations and major gifts. We organize our work in two‑week sprints, with consistent backlog reviews, sprint planning, mid‑sprint reviews, and sprint retros.
You’ll be joining at an important juncture for both the analytics team and the Foundation. We’ve recently completed an infrastructure migration to a more performant analytics stack and equipped our stakeholders with a self‑serve reporting platform, so we’re well set up for working on the most important questions to fundraising. The web traffic landscape is changing quickly, and Wikimedia continues to diversify its fundraising channels and evaluate new approaches. Analytics partners in this work model scenarios, give fundraising teams visibility and alerting into trends, advise on experiments for evaluating new strategies, bring in and model new data sources, and do timely ad hoc analysis so that teams can quickly learn and iterate.
Our updated stack includes dbt, Metabase, and Jupyter notebooks. Our lakehouse data infrastructure is built on MinIO for storage, using Apache Iceberg table format and Trino as query engine. Code reviews are currently in Gerrit and moving to GitLab.
Responsibilities
Deliver insights and analysis on global fundraising campaigns and fundraising strategic objectives to fundraising teams.
Develop and track key performance indicators across different fundraising channels.
Partner with colleagues in fundraising and finance on multi‑year revenue forecasting.
Deliver reporting, statistical analysis, and guidance on testing within our iterative A/B testing program.
Model the data upstream of your reporting and analysis, cleaning and transforming it in dbt.
Peer review teammates’ work to ensure data quality and interpretability.
Examples of the work you may do in the role
Build and maintain a donor propensity model to drive revenue across the fundraising program.
Build out donor segments in an audience‑building tool such as Hightouch.
Build a model to personalize ask amount for a donor.
Qualifications
Experienced in fundraising analytics, ideally in a large, international fundraising program.
Experience analyzing digital marketing campaigns.
Technical Skills
Highly proficient in SQL for data modeling and analytical queries.
Skilled in developing clear data visualizations in a business intelligence platform.
Practical statistical expertise for designing experiments and drawing valid conclusions from experimental results.
Comfortable working with Python for more advanced calculations or analysis.
Experience using predictive modeling to answer “business” questions.
Experience efficiently troubleshooting SQL queries and pipelines to find root cause of a data anomaly.
Comfortable with giving and receiving code reviews through git (GitLab, GitHub, Gerrit, etc.).
Record of clearly documenting work for the benefit of teammates and stakeholders.
Record of estimating work accurately and surfacing obstacles to on‑time delivery in a timely way.
Practice of reaching out for support when stuck or blocked.
Growth mindset, enjoyment of experimenting with new tools and methods.
Excellent verbal and written communication skills, including the ability to clearly communicate technical concepts to non‑technical stakeholders.
Experience in a remote work environment.
Qualities that are Important to Us
Strong mission fit with the Wikimedia movement (e.g., freedom of speech, knowledge for everyone, community sharing).
Strong value fit with Wikimedia Foundation values (e.g., collaboration, curiosity, knowledge sharing).
Ability to work effectively across cultures.
Additionally, we’d love it if you have:
Experience with open source technologies and communities.
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  • United States

Compétences linguistiques

  • English
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