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 plannings, 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 by modeling scenarios, giving fundraising teams visibility and alerting into trends, advising on experiments for evaluating new strategies, bringing in and modeling new data sources, and doing 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.
You are responsible for:
Delivering insights and analysis on global fundraising campaigns and fundraising strategic objectives to fundraising teams
Developing and tracking key performance indicators across different fundraising channels
Partnering with colleagues in fundraising and finance on multi-year revenue forecasting
Delivering reporting, statistical analysis, and guidance on testing within our iterative A/B testing program
Modeling the data upstream of your reporting and analysis, cleaning and transforming it in dbt
Peer reviewing your teammates’ work to ensure data quality and interpretability
Some examples of the work you may do in the role:
Building and maintaining a donor propensity model to drive revenue across the fundraising program
Building out donor segments in an audience-building tool such as Hightouch
Building a model to personalize ask amount for a donor
Skills and Experience:
Subject matter expertise
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 the root cause of a data anomaly
Collaboration
Comfortable with giving and receiving code reviews through git (GitLab, GitHub, Gerrit, etc.)
A record of clearly documenting your work for the benefit of your teammates and stakeholders
A record of estimating work accurately and surfacing obstacles to on-time delivery in a timely way
A practice of reaching out for support when stuck or blocked
A growth mindset, enjoy 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
