Senior Data Scientist, Safety & Security
Wikimedia · Remote
About this role
**Summary** Wikipedia is a trusted, free knowledge source operated by the non-profit Wikimedia Foundation. We’re hiring a **Senior Data Scientist (Safety & Security)** to help guide Wikipedia’s anti-abuse and security strategy as part of our **Product Analytics** team. In this role, you’ll partner with product managers, engineers, and others to ensure our safety and security efforts measurably improve product outcomes. You’ll work closely with the **Product Safety and Integrity** team, applying cutting-edge AI and machine learning to difficult safety/security problems. **What you’ll work on (examples)** - Define how we measure success for detecting bots and inauthentic account activity (e.g., sockpuppetry). - Provide analysis to inform new heuristics and approaches for detecting potentially abusive activity. - Collaborate with research scientists and security engineers to develop and evaluate AI models to find malicious user-authored code. **Important note** This role requires availability for critical meetings and synchronous collaboration between **13:00 and 19:00 UTC**. **You’ll be responsible for** - Serving as a strategic partner to product teams across functions. - Making proactive recommendations on product direction and data strategy; surfacing insights and interpreting results. - Delivering accurate quantitative insights to guide strategy and assess impact—balancing rigor with a fast-changing environment. - Communicating results clearly to stakeholders and supporting data-backed decision-making. - Building and executing measurement strategy, evaluating experiments using **Bayesian and Frequentist** approaches, and conducting quantitative research. - Developing queries and code for large-scale internal/external data using tools such as **Apache Iceberg, Hive, Druid, Presto, and Spark** (and AI coding assistants). - Building automated, self-service dashboards (e.g., **DBT, Airflow, Superset**) to track success and health metrics. - Helping teams instrument features, perform data quality assurance, and support A/B testing. - Using good judgment to prioritize work and select appropriate analytical methods. **Skills & experience** - Experience with experimental design and statistics or machine learning. - Experience using AI coding assistants for data analysis and technical tasks. - Fluency in **R or Python**, plus common version control and command-line tools. - Fluency in **SQL** and experience with large-scale data (e.g., Hive, Presto, Druid, Spark). - Experience collaborating with product teams in a fast-paced environment to test, analyze, and evaluate user-facing features. **Qualities we value** - Ability to explain data and insights clearly to non-specialists. - Curiosity and critical thinking; a lifelong learner who can view problems from multiple angles. - Empathy and commitment to Wikimedia volunteer communities; discretion with sensitive/confidential data. - Commitment to the Wikimedia Foundation mission, values, and guiding principles. - Self-motivation and comfort navigating ambiguity and complexity. **Nice to have** - Experience in trust & safety, information security/privacy, or fraud/anti-abuse. - Interest in ethical data management and privacy practices. - Contribution to Wikimedia or other open-source projects. - Experience with tools like **Superset** or **Growthbook** (or similar open-source testing/visualization/reporting tools). **About the Wikimedia Foundation** The Wikimedia Foundation is the nonprofit
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