Data Scientist, Data Insights
At Docker, we make app development easier so developers can focus on what matters. Our remote-first team spans the globe, united by a passion for innovation and great developer experiences. With over 20 million monthly users and 20 billion image pulls, Docker is the #1 tool for building, sharing, and running apps—trusted by startups and Fortune 100s alike. We’re growing fast and just getting started. Come join us for a whale of a ride!
Docker is seeking a 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.
This is a hands-on analytical role focused on independent execution, deep-dive analysis, and translating complex data into clear business recommendations. You'll work closely with Product Managers, Executive Leaders, and Engineering teams to define key metrics, measure product health, and inform data-driven decisions.
Success in this role requires a strong foundation in statistics, advanced SQL skills, and proven experience in product experimentation and reporting for a technical audience.
Responsibilities
Product Analytics & Experimentation
Understand detailed usage of Docker products by analyzing user behavior data, translating complex questions into analytical plans, and building robust product metrics.
Run and measure product experiments (A/B tests) from design through interpretation, clearly articulating results and recommendations to stakeholders.
Develop and maintain key performance indicators (KPIs) and operational metrics for product features and overall business health.
Strategic Insights & Reporting
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.
Technical Execution & Modeling
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.
Collaboration & Communication
Partner with cross-functional teams (Product, Engineering, Marketing, Sales) to define data requirements and analytical objectives.
Mentor junior analysts on best practices for data visualization, statistical analysis, and clear communication of results.
Qualifications
Required:
Technical Expertise
3+ years of experience in a Data Scientist or Product Analyst role, preferably within a technology or SaaS company.
Expert proficiency in SQL for complex data extraction and manipulation.
Strong proficiency in a statistical programming language (Python or R), including libraries for data manipulation, analysis, and statistical modeling.
Proven experience designing, launching, and analyzing A/B tests or other product experiments.
Experience with cloud data warehouses (e.g., Snowflake, Redshift, BigQuery) and data visualization tools (e.g., Sigma, Tableau, Looker).
Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
Analytical & Statistical Foundations
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.
Communication & Leadership
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.
Preferred:
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).
Key Success Metrics
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.
Docker does not offer visa sponsorship for this role.
We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on April 13, 2024.
Please see the independent bias audit report covering our use of Covey here.
Perks
Freedom & flexibility; fit your work around your life
Designated quarterly Whaleness Days plus end of year Whaleness break
Home office setup; we want you comfortable while you work
16 weeks of paid Parental leave
Technology stipend equivalent to $100 net/month
PTO plan that encourages you to take time to do the things you enjoy
Training stipend for conferences, courses and classes
Equity; we are a growing start-up and want all employees to have a share in the success of the company
Docker Swag
Medical benefits, retirement and holidays vary by country
Remote-first culture, with offices in Seattle and Paris
Docker embraces diversity and equal opportunity. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills. The more inclusive we are, the better our company will be.
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