Senior Data Scientist, Ecosystems

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Overview

Summary As a Senior Data Scientist, you will bridge the gap between complex datasets and strategic action. You’ll synthesize information from various external sources such as Google Search Console, Semrush, AHRefs, Matomo, as well as WMF’s data lake to develop visibility and insights into search…

Requirements Summary

Fluent in Python and Jupyter for data analysis, statistical modeling, simulation, visualization & reporting. Fluent in SQL and working with large scale data using tools such as Hive, Presto, Druid, and Spark.

Technical Tools

bigquerypythonsqlab-testingdata-analysisstatistical-modeling

As a Senior Data Scientist, you will bridge the gap between complex datasets and strategic action. You’ll synthesize information from various external sources such as Google Search Console, Semrush, AHRefs, Matomo, as well as WMF’s data lake to develop visibility and insights into search recall gaps and emerging topic trends. Your mission is to provide leadership with the clarity needed to make confident, informed decisions.

You will help inform Wikimedia’s strategy for ensuring that people continue to find the content they need from the Wikipedias and other wiki projects, as well as on the Wikimedia Foundation’s sites. You will provide visibility into web analytics, search trends, content trends, patterns of usage, and search recall gaps.

As a Senior Data Scientist, you will be the primary architect of our search and visibility insights. You will be responsible for:

Integrating fragmented data from our internal data lake, BigQuery, Matomo, and external intelligence tools such as Ahrefs, Semrush, and Trakkr AI among others to create a unified, granular view of how users discover and use our content across desktop and mobile domains.
Translating analytics and complex trends by geography, project, and topic into actionable narratives that help leadership navigate uncertainty and prioritize high-impact interventions.
Developing automated systems to detect where our content is under-indexed or missing from results, providing the data necessary to improve article coverage, alternative titles, content for the Wikimedia Foundation’s websites, and FAQ structures.
Establishing the metrics and frameworks to track how our content is utilized within Large Language Models and generative search engines, directly informing high-level negotiations and the valuation of our Enterprise offerings, as well as driving grassroot donor growth.
Defining Measurable Outcomes: Collaborating with product leaders to set achievable goals and drafting the instrumentation requirements necessary to track success with technical precision.
Assessing the efficacy of new initiatives through the rigorous design and analysis of experiments (e.g., A/B testing) to understand their true impact on our global audience.
Interpreting website performance data to uncover insights, inform UX/UI enhancements, and support strategies aimed at improving customer experience and conversion outcomes on the Wikimedia Foundation’s websites.

Requirements

~1 min read

Fluent in Python and Jupyter for data analysis, statistical modeling, simulation, visualization & reporting.
Fluent in SQL and working with large scale data using tools such as Hive, Presto, Druid, and Spark.
Experience with building dashboards & reports using tools such as Jupyter, Quarto, Superset.
A solid, intuitive understanding of how websites operate (including structure, user journeys, and tracking mechanisms), combined with practical expertise in web search SEO/GEO.
A Bachelor’s degree + 5 years related experience or a Master’s degree + 3 years related experience; or equivalent work experience.

Excellent communication skills.
You must possess the statistical nuance required to design experiments, identify statistically significant phenomena, and frame findings into clear, high-level narratives.
Comfortable working in a highly collaborative, remote environment.

Familiarity with Wikimedia projects, moderation processes, and communities.

The Wikimedia Foundation is the nonprofit organization that 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 freely. We host Wikipedia and 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 donations 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.

As an equal opportunity employer, the Wikimedia Foundation values having a diverse workforce and continuously strives to maintain an inclusive and equitable workplace. We encourage people with a diverse range of backgrounds to apply. We do not discriminate against any person based upon their race, traits historically associated with race, religion, color, national origin, sex, pregnancy or related medical conditions, parental status, sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, or any other legally protected characteristics.

The Wikimedia Foundation is a remote-first organization with staff members including contractors based 40+ countries*. Salaries at the Wikimedia Foundation are set in a way that is competitive, equitable, and consistent with our values and culture. The anticipated annual pay range of this position for applicants based within the United States is US$106,227 to US$167,858 with multiple individualized factors, including cost of living in the location, being the determinants of the offered pay. For applicants located outside of the US, the pay range will be adjusted to the country of hire. We neither ask for nor take into consideration the salary history of applicants. The compensation for a successful applicant will be based on their skills, experience and location.