Data Scientist

• Gather, preprocess, and validate datasets from internal and external sources.
• Identify trends, patterns, and anomalies using statistical and visual techniques.
• Build and evaluate predictive models using machine learning algorithms.
• Create dashboards and visual reports to communicate findings to stakeholders.
• Maintain clear records of methodologies, code, and project outcomes.
• Work closely with cross-functional teams to align data solutions with business needs.

Data Science, AI Intern

• Bridge the gap between complex datasets and strategic action.
• Synthesize information from various external sources to develop visibility and insights into search recall gaps and emerging topic trends.
• Inform Wikimedia’s strategy for ensuring that people continue to find the content they need.
• Integrate fragmented data to create a unified view of how users discover and use content.
• Translate analytics and complex trends into actionable narratives.
• Develop automated systems to detect under-indexed content.
• Establish metrics and frameworks for content utilization within Large Language Models.
• Collaborate with product leaders to set goals and track success.
• Assess efficacy of new initiatives through experiment design and analysis
• Interpret website performance data to inform UX/UI enhancements.

Senior Data Scientist, Ecosystems

• Leverage a broad range of techniques to turn data into actionable business insights
• Tackle complex analytical problems and uncover trends
• Operate in a fast-paced environment managing projects end-to-end
• Work with stakeholders to identify opportunities for leveraging company data
• Mine and analyze data to drive optimization and improvement
• Develop custom data models and algorithms
• Communicate business requirements to ensure buy-in from all departments
• Participate in projects to provide data and analyses as needed

• Serve as an embedded data lead:
• Understand the product – strategy, goals, roadmap, users – deeply enough to identify high-impact, strategic opportunities and risks.
• Use data to steer conversations: bring data-driven hypotheses, challenge assumptions, frame trade-offs, prioritize strategically.
• Translate vague product hunches into sharp analytical questions, and design the right approach to answer them.
• Be the source of truth for KPIs and product metrics: help define and monitor them, and identify trends and drivers.
• Drive decisionmaking with data: Prioritize analyses that meaningfully inform product decisions and change outcomes, reframe analysis requests that won’t do that into ones that will, and design and deliver the resulting analyses properly and rapidly.
• Lead experimentation thoughtfully: guide the team on when and when not to experiment, help enable self-serve experimentation, and focus on frequent, small experiments to speed learning.
• Identify where product strategy and ideas could be better, more easily, or more quickly implemented with the help of AI (ML or GenAI), and help enable this integration.
• Show up as a collaborative leader, not simply a service provider, and help focus work on what matters most.
• Work end-to-end to translate clinical, member, and claims data from our data warehouse into actionable recommendations: work with stakeholders to design reports and dashboards that answer real business questions, design the data flows to support these, and build the required data transformation pipelines.

Senior Data Scientist

• Support data collection, cleaning, transformation, and exploratory analysis for ongoing projects.
• Assist in developing, testing, and improving machine learning and LLM models.
• Perform deep-dive analysis to evaluate model behavior, output quality, and performance across different approaches.
• Help refine prompts, evaluation criteria, and testing workflows to improve consistency and outcomes.
• Partner with cross-functional teams to translate business questions into analytical solutions.
• Build reports, visualizations, and dashboards to communicate insights to technical and non-technical stakeholders.
• Document methods, experiment results, and recommendations clearly and thoroughly.
• Participate in team meetings, project discussions, and implementation reviews.

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Data Science, AI Intern

Senior Data Scientist, Ecosystems

Data Scientist

Senior Data Scientist

Innovation, Data Science Internship