Senior Data Scientist, Data Insights

Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout.

We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default.

Docker is seeking a Senior Data Scientist to join our Data Insights team. You will be a key individual contributor, applying statistical rigor and advanced analytical techniques to extract value from our product and business data. This role requires a strong understanding of product usage to provide actionable insights that drive business strategy and feature development.

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  Understand detailed usage of Docker products by analyzing user behavior data, translating complex questions into analytical plans, and building robust product metrics.

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  Run and measure product experiments (A/B tests) from design through interpretation, clearly articulating results and recommendations to stakeholders.

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  Develop and maintain key performance indicators (KPIs) and operational metrics for product features and overall business health.

• Provide actionable insights for Product Managers on user engagement, feature adoption, and growth opportunities to directly inform the product roadmap.

• Build deep-dive reports for Executive Leaders on critical business trends and the performance of strategic initiatives, presenting findings in a clear, compelling narrative.

• Collaborate with engineering teams on data logging, instrumentation, and ensuring the accuracy of product data pipelines.

• Influence product and business strategy by framing data-informed tradeoffs and recommendations for senior leaders.

• Apply statistical modeling and machine learning techniques to solve business problems (e.g., churn prediction, segmentation, propensity modeling).

• Design and implement data visualizations and self-service dashboards to democratize data access across the organization.

• Ensure data quality and integrity for all analytical outputs and reports.

• Partner with cross-functional teams (Product, Engineering, Marketing, Sales) to define data requirements and analytical objectives.

• Coach and mentor junior analysts and data scientists on best practices for data visualization, statistical analysis, and clear communication of results.

• Advanced knowledge of statistical methods (regression, hypothesis testing, time series analysis) and their application to business problems.

• Demonstrated ability to translate open-ended business questions into structured analytical projects and deliverables.

• Excellent verbal and written communication skills, with the ability to present complex analytical findings to both technical and executive audiences.

• Demonstrated ability to work independently and drive projects from conception to completion with minimal supervision.

• Proven experience influencing senior stakeholders and driving alignment on data-informed decisions.

• Experience analyzing data related to developer tools or B2B SaaS products.

• Advanced degree (M.S. or Ph.D.) in a quantitative field such as Statistics, Computer Science, Economics, or Mathematics.

• Knowledge of container technologies (Docker, Kubernetes).
  

• Impact of actionable insights on product feature adoption and business revenue.

• Quality and clarity of executive-level deep-dive reports.

• Successful design and interpretation of product experiments.

• Demonstrated independence in driving analytical projects.

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