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Sr. Data Analyst

Rolling Deadline  |  Full-Time Job  |  Telecommute

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Location: San Francisco, CA or Remote

Summary

The Product Analytics team at Wikimedia is a collaborative team with organizational-wide impact. We provide quantitatively-based user insights to improve decision-making throughout Wikimedia, with a focus on supporting product decisions that benefit our global community of users. Our team is passionate about ensuring our work is impactful, accessible, reliable, and ethically sourced & applied.

We’re looking for a Senior/Lead Data Analyst who will advance our mission of informing organization-wide strategies by distilling complex data down to key takeaways. You will shape the way we automate, report on, and share data. The insights you generate will impact one of the most relied-upon digital platforms in the world, and your work will support a non-profit organization dedicated to free knowledge for everyone. 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:

  • Lead efforts to identify and define key metrics for measuring progress against organizational and project goals.
  • Proactively identify requirements to support and improve an evolving data ecosystem.
  • Collaborate with product, business, and technology teams to ensure that data collection and calculation of metrics are appropriately implemented.
  • Cultivate a culture of self-service reporting by standardizing and communicating key metrics, building dashboards and analytical tools, and guiding stakeholders in how to interpret the data.
  • Write database queries and code to analyze Wikipedia usage volume, user behaviour, and performance data to identify opportunities and areas for improvement.
  • Work with large scale data, using & evaluating 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.

We’d love to hear from you if you:

  • Have advanced professional experience using analytics tools and infrastructure to extract patterns from large and complex datasets.
  • Are able to communicate findings and recommendations clearly to colleagues with diverse backgrounds and areas of expertise.
  • Are disciplined and data-aware with a strong desire to test, learn, and iterate.
  • Have a track record of building repeatable analyses that balance precision with interpretability.
  • Have a strong working knowledge of SQL.
  • Are familiar with using Python, R, or other scripting languages for data analytics tasks.
  • Are flexible and open to change and new information
  • Are comfortable working in a highly collaborative, consensus-oriented environment.
  • Have a bachelor’s degree in a related field or the equivalent in relevant work experience

Extra bonus points for experience with any of the following:

  • Large-scale data processing & storage tools (we use Hadoop, Hive/Presto, Spark, and Druid)
  • Open source technologies
  • Data governance
  • Web/digital analytics
  • Applied statistical methods

When applying, please make sure your application includes a brief cover letter which states why you are interested in this position and what you would bring to Wikimedia.

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

More information

Wikimedia Foundation website

Wikimedia Foundation blog

Annual Report – 2017

Wikimedia 2030

Date posted:

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