Senior Data Scientist, Ecosystems

About the Role

The role entails working closely with cross-functional teams, including product, engineering, and marketing, to inform Wikimedia's strategy for ensuring that people continue to find the content they need from the Wikipedias and other wiki projects. You will provide visibility into web analytics, search trends, content trends, patterns of usage, and search recall gaps.

What You Will Do

• Integrate fragmented data from internal and external sources, including BigQuery, Matomo, Ahrefs, and Semrush, to create a unified, granular view of user behavior across desktop and mobile domains.
• Translate analytics and complex trends by geography, project, and topic into actionable narratives that help leadership navigate uncertainty and prioritize high-impact interventions.
• Develop automated systems to detect where content is under-indexed or missing from results, providing the data necessary to improve article coverage, alternative titles, and content structures.
• Establish metrics and frameworks to track how content is utilized within Large Language Models and generative search engines, directly informing high-level negotiations and the valuation of Enterprise offerings.
• Define measurable outcomes by collaborating with product leaders to set achievable goals and drafting instrumentation requirements necessary to track success with technical precision.
• Assess the efficacy of new initiatives through the rigorous design and analysis of experiments, such as A/B testing, to understand their true impact on the global audience.
• Interpret website performance data to uncover insights, inform UX/UI enhancements, and support strategies aimed at improving customer experience and conversion outcomes on Wikimedia Foundation's websites.
• Work closely with product leaders to identify areas for improvement and develop data-driven solutions to enhance user engagement and content discoverability.

What We Are Looking For

• A Bachelor's degree in Computer Science, Statistics, or a related field, with at least 5 years of experience in data science, or a Master's degree with at least 3 years of experience.
• Fluency in Python and Jupyter for data analysis, statistical modeling, simulation, visualization, and reporting.
• Experience with SQL and working with large-scale data using tools such as Hive, Presto, Druid, and Spark.
• Practical expertise in web search SEO/GEO, including understanding of website structures, user journeys, and tracking mechanisms.
• Excellent communication skills, with the ability to design experiments, identify statistically significant phenomena, and frame findings into clear, high-level narratives.
• Comfort working in a highly collaborative, remote environment, with experience in building dashboards and reports using tools such as Jupyter, Quarto, and Superset.
• Strong understanding of data visualization principles and the ability to communicate complex data insights to non-technical stakeholders.

Nice to Have

• Familiarity with Wikimedia projects, moderation processes, and communities.
• Experience with Adjust and SEMrush for mobile app and web analytics.
• Knowledge of machine learning algorithms and their application in data analysis.
• Participation in open-source projects or contributions to public datasets.

Benefits and Perks

• The opportunity to work on a global, high-impact project that promotes free knowledge and education.
• Collaboration with a talented, international team of professionals.
• Flexible, remote work arrangements that allow for a healthy work-life balance.
• Professional development opportunities, including access to training and conferences.
• A comprehensive benefits package, including health insurance, retirement planning, and paid time off.
• The chance to work with a wide range of technologies and tools, including cutting-edge data analytics platforms.

• Develop a strong portfolio showcasing your data analysis and visualization skills, particularly with tools like Python, Jupyter, and SQL.
• Highlight your experience working with external data sources, such as Google Search Console and SEMrush, to demonstrate your ability to integrate and analyze complex datasets.
• Prepare to discuss your approach to experiment design and analysis, including how you identify statistically significant phenomena and communicate findings to non-technical stakeholders.
• Familiarize yourself with Wikimedia's projects and initiatives to demonstrate your passion for the organization's mission and values.
• Be prepared to discuss your experience working in a remote, collaborative environment and how you handle communication and project management in a distributed team.
• Research the current market rate for data scientists in the non-profit sector to negotiate a competitive salary.