Data Analyst (Mobile Apps & Product)
The Wikimedia Foundation is looking for a Data Analyst to join our team, reporting to the Head of Product Analytics. The Product Analytics team is a collaborative team with organization-wide impact. We provide quantitatively based user insights to improve decision-making within the Foundation and the Wikimedia Movement. Our focus is on supporting product decisions that enable our communities to achieve Wikimedia’s vision: a world in which every single human being can freely share in the sum of all knowledge.
We’re looking for a Data Analyst who will advance our team’s mission of informing decisions by providing impactful, accessible, and ethical data and insights. In this role, you will help our iOS and Android mobile apps teams improve Wikipedia editor and reader experiences by analyzing user behavior and identifying impacts from product tests. You’ll work with product teams to ensure that tagging and metrics are appropriately defined and implemented, and promote best practices for measuring user behavior across our websites and mobile apps.
The insights you generate will impact one of the most relied-upon digital platforms in the world, and your work will support our strategic direction toward service and equity. Our commitment to user privacy sets Wikimedia sites apart from almost all major websites, and inspires creative approaches to our data work.
In this role, you will:
- Identify key metrics for measuring progress against product and organizational goals.
- Collaborate with product, business, and technology teams to ensure that tagging and metrics are appropriately implemented.
- Work with data and metrics in App Store Connect, Play Store Console, and App Annie that supplement our internal analytics solutions.
- Build data visualizations, reports, and dashboards, and guide stakeholders in how to interpret the data.
- Design, execute, and evaluate experiments and quantitative research to inform product decisions.
- Analyze Wikipedia usage volume, user behavior, and performance data to identify opportunities and areas for improvement.
- Work with large-scale data, using tools such as Hadoop, Hive/Presto, Druid, Superset, Turnilo, Spark, and Jupyter.
- Communicate data insights clearly and responsively to a range of departmental, organisational, volunteer, and public stakeholders.
Skills and Experience:
- Experience with tracking and analytics on consumer, mass media, or social network mobile apps and websites. (Our tracking system is homegrown, but prior experience with tools like Google Analytics, Mixpanel, Adobe Analytics, etc. is helpful.)
- Comfortable using analytics tools and scripting languages to create reports that blend data from multiple sources (our team frequently uses Python or R, Hadoop, Hive/Presto, Spark, and Druid).
- Ability to communicate findings and recommendations clearly to colleagues with diverse backgrounds and areas of expertise.
- Strong working knowledge of SQL.
- Bachelor’s degree in a related field or the equivalent in relevant work experience.
Qualities that are important to us:
- Flexible and open to change and new information.
- Comfortable working in a highly collaborative, consensus-oriented environment.
Additionally, we’d love it if you have any of the following:
- Fluency in a language other than English (our apps teams are interested in expanding our reach in Asia, Africa, and Latin America).
- Experience with open source technologies and communities.
- Experience contributing to Wikimedia projects.
The Wikimedia Foundation is...
...the nonprofit organization that hosts and operates Wikipedia and the other Wikimedia free knowledge projects. Our vision is a world in which every single human can freely share in the sum of all knowledge. We believe that everyone has the potential to contribute something to our shared knowledge, and that everyone should be able to access that knowledge, free of interference. We host the Wikimedia projects, build software experiences for reading, contributing, and sharing Wikimedia content, support the volunteer communities and partners who make Wikimedia possible, and advocate for policies that enable Wikimedia and free knowledge to thrive. The Wikimedia Foundation is a charitable, not-for-profit organization that relies on donations. We receive financial support from millions of individuals around the world, with an average donation of about $15. We also receive donations through institutional grants and gifts. The Wikimedia Foundation is a United States 501(c)(3) tax-exempt organization with offices in San Francisco, California, USA.
The Wikimedia Foundation is an equal opportunity employer, and we encourage people with a diverse range of backgrounds to apply.
U.S. Benefits & Perks*
- Fully paid medical, dental and vision coverage for employees and their eligible families (yes, fully paid premiums!)
- The Wellness Program provides reimbursement for mind, body and soul activities such as fitness memberships, baby sitting, continuing education and much more
- The 401(k) retirement plan offers matched contributions at 4% of annual salary
- Flexible and generous time off - vacation, sick and volunteer days, plus 19 paid holidays - including the last week of the year.
- Family friendly! 100% paid new parent leave for seven weeks plus an additional five weeks for pregnancy, flexible options to phase back in after leave, fully equipped lactation room.
- For those emergency moments - long and short term disability, life insurance (2x salary) and an employee assistance program
- Pre-tax savings plans for health care, child care, elder care, public transportation and parking expenses
- Telecommuting and flexible work schedules available
- Appropriate fuel for thinking and coding (aka, a pantry full of treats) and monthly massages to help staff relax
- Great colleagues - diverse staff and contractors speaking dozens of languages from around the world, fantastic intellectual discourse, mission-driven and intensely passionate people
*Eligible international workers' benefits are specific to their location and dependent on their employer of record
Python, iOS, Android, SQL, and R
8 days ago - source