As a Senior Data Scientist for Product at CircleCI, you will:

  • Be a thought leader in using data to improve CI/CD practices
  • Build and deploy models supporting product features that help 100,000+ developers ship code faster
  • Coach a team of mid-to-senior-level product analysts to improve data-science skills
  • Build company-wide practices to enable model discovery, deployment, monitoring, and governance

About Product’s Data Science and Analytics team at CircleCI

You will be a member of CircleCI’s 10-member Analytics and Data Science team. You will report to the team’s director. The team is part of CircleCI’s product organization. The team is focused on improving our product experience, enabling data-driven product management, and improving company-wide data practices. You will partner with product managers and leaders. You will collaborate with Data Engineering, Analytics Engineering, Design, and other stakeholders.

What you’ll do:

  • Discover models that solve CI/CD’s hardest problems: Work with product managers to quantitatively identify customers’ CI/CD pain points, like slow builds, flaky tests, and dependency hell, and to help make product decisions. Work with engineering leads to identify platform optimizations, like capacity allocation and demand forecasting. Prioritize problems. Engage in exploratory data analysis. Evaluate available data and define requirements for needed data. Select modeling strategies, tools, and approaches Build features and tune models. Present to stakeholders and executives. (Approximately 40% of your time).
  • Mentor analysts and build team practices: Be an effective coach. Improve teammates’ data-science skills, such as modeling strategy, feature engineering, and model scoring. Improve teammates’ analytics skills across a variety of problems. Help groom business questions, evaluate data sources, identify analytical techniques, and create visualizations. Up-level the team’s programming skills. Build processes to help the team scale. Improve the team’s use of statistics, hypothesis testing, and experimental design. Keep the team up-to-date on the state of the art. (Approximately 30% of your time).
  • Build data practices: Define a process for the discovery of data products. Collaborate with data engineering and business intelligence on ingesting data, pipelining appropriate features, and rolling models into production. Contribute to our growing data architecture, governance, documentation, and security practices. Work through organizational, people, and process challenges of breaking new ground. Celebrate incremental wins. (Approximately 30% of your time).

What we’re looking for:

  • Data science experience: Six or more years in data science, analytics, or comparable roles. Four or more years focused on models and algorithms. Demonstrable experience with model selection. Creativity in adapting tools and techniques.
  • Instinct for product discovery: Experience with product management and the discovery of data products. Effective data-product prototyping. Able to uncover insights in messy data sources. Effective juggler of scope, time, and value. Able to build cross-functional partnerships.
  • Analytics leader: Experience mentoring and developing teammates. Fostered open, respectful, data-driven team cultures. Smartly managed hard technical and business trade-offs. Defined effective and flexible best practices.
  • Strong technical education: Ideally, a Master’s degree in a technical or quantitative field such as Statistics, Mathematics, Computer Science, Engineering, Economics, or Finance. Bonus for relevant Ph.D.
  • Big-data, cloud-based toolkit: Worked with billion-row datasets. Experienced with distributed data processing technology (e.g., Spark). Hands-on experience with AWS’s data warehousing and ML products and Snowflake. Fluent in Python for analytics/ML use cases as well as SQL.
  • Right soft skills: Passion for data, discovery, and problem-solving. Curious; confident; and open to questioning assumptions and being questioned. Effective communicator across technical and business audiences; able to manage stakeholder expectations; and able to collaborate with hands-on executives. Entrepreneurial; fast-moving; able to balance vision with execution; and not easily discouraged. Has an instinct for value; and focused on the incremental, not gold plating.
  • Bonus for knowledge of our domain–software delivery: Empathy for the challenges developers face with productivity and time to market. Ideally, experience developing code, debugging, testing, committing with distributed VCS and modern CI/CD.
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