How to apply for Senior Data Scientist, Safety & Security

About Wikimedia

The Wikimedia Foundation is the non-profit that operates Wikipedia, one of the most trusted and visited knowledge resources in the world, serving over a billion people monthly in more than 300 languages. Unlike ad-driven tech companies, Wikimedia is funded primarily by small donations and is committed to independence, transparency, and community-driven governance. Working here means contributing to a mission-driven organization where your work directly supports free, open knowledge for everyone.

About the role

As a Senior Data Scientist on the Product Analytics team, you will focus on safety and security, partnering closely with the Product Safety and Integrity team to inform anti-abuse and security strategies. You will design metrics, conduct creative analyses, and develop data strategies to measure the impact of interventions against bots, sockpuppetry, and other threats. Your work will directly shape how Wikipedia detects and mitigates abuse, ensuring the platform remains reliable and trustworthy in an evolving online landscape.

A typical day

A typical day might involve collaborating with product managers and engineers to define metrics for a new anti-abuse feature, analyzing edit data to identify patterns of sockpuppetry, and presenting findings to stakeholders to inform strategy. You might also spend time writing SQL queries, building statistical models, or reviewing dashboards to monitor the health of safety interventions. Expect frequent cross-functional meetings and asynchronous communication in a fully remote environment.

Who Wikimedia is looking for

• Proven experience in data science with a focus on trust & safety, security, or integrity, including designing metrics for abuse detection and mitigation.
• Strong proficiency in SQL and Python/R for statistical analysis and modeling, with experience handling large, complex datasets in distributed environments (e.g., Spark, Hive).
• Ability to translate ambiguous safety and security problems into measurable data questions and communicate findings to both technical and non-technical stakeholders.
• Familiarity with Wikipedia's editing model, community dynamics, and challenges like sockpuppetry and vandalism, or a demonstrated ability to quickly learn complex socio-technical systems.

Tips for this application

• Highlight any experience you have with trust and safety analytics, especially in platforms with user-generated content; specifically mention metrics you've developed to detect inauthentic behavior.
• Demonstrate familiarity with Wikimedia's editing community and challenges (e.g., sockpuppetry, bot detection) by referencing specific examples or research in your application.
• Emphasize your ability to work remotely and collaboratively across time zones, as Wikimedia is a distributed organization with a strong remote culture.
• Showcase your skills in statistical modeling and experimentation, and how you've used them to inform product decisions in safety contexts.
• Tailor your resume to include keywords from the job description such as 'anti-abuse', 'sockpuppetry', 'product analytics', and 'safety & security' to pass initial screenings.

What to cover in your cover letter

In your cover letter, emphasize your passion for Wikimedia's mission and how your data science skills can protect its integrity. Discuss specific projects where you developed metrics or models to detect abuse or security threats, and how you communicated insights to drive product strategy. Highlight your ability to collaborate with cross-functional teams, especially product managers and engineers, to implement data-informed solutions. Finally, mention any experience with open-source communities or volunteer-driven platforms, as it demonstrates cultural alignment.

Research before applying

• Explore Wikimedia's Product Analytics team and their past work on safety and security, such as blog posts or research papers on vandalism detection or sockpuppetry.
• Understand Wikipedia's editing model, including the roles of bots, administrators, and checkusers, and the challenges they face in maintaining integrity.
• Read about Wikimedia's 2030 strategy and their current initiatives around AI and machine learning for safety, as mentioned in the job description.
• Familiarize yourself with Wikimedia's technical stack and data infrastructure (e.g., Hadoop, Spark, Superset) to understand the tools you'll be working with.

Likely interview topics

Based on the job description, expect questions about:

• How would you measure the success of efforts to detect sockpuppetry on Wikipedia? Walk us through the metrics you'd choose and why.
• Describe a time when you used data to influence a product decision related to safety or security. What was the outcome?
• What statistical methods would you use to identify anomalous editing behavior, and how would you validate your findings?
• How would you collaborate with engineers to implement a machine learning model for abuse detection, and what challenges might arise?
• Given Wikipedia's global and multilingual context, how would you ensure your analyses account for cultural and linguistic differences in abuse patterns?

Common mistakes to avoid

• Avoid generic cover letters that don't mention Wikimedia's unique non-profit, community-driven model; candidates often fail to show genuine interest in the mission.
• Do not focus solely on technical skills without demonstrating an understanding of the socio-technical aspects of safety and security in open communities.
• Avoid proposing solutions that would compromise user privacy or community trust; Wikimedia values transparency and privacy, so suggesting invasive data collection methods would be a red flag.