Senior Data Analyst, Product

Summary

Join CircleCI's Data Science and Analytics team as a Senior Data Analyst, Product, and lead all things data for your product team! You will uncover business questions, develop hypotheses, write research plans, explore data, use statistics, create visualizations, and present insights to various audiences. Collaborate with product managers, designers, and engineers to define, root cause, and forecast product metrics. Utilize a growth toolkit, focusing on product activation, engagement, retention, and growth, and support iterative cycles of build, measure, and learn. Improve the analytics practice by turning repetitive analyses into dashboards, improving team processes, building data pipelines, and defining requirements for better data. This role requires 2-5 years of product analytics experience at a high-growth company, a bachelor's degree in a technical or quantitative field, and proficiency in analytical SQL, Python with Pandas, and intermediate statistics. The position offers remote work options throughout North America.

Requirements

• Two to five years of product analytics: Successful candidates typically have from two to five years supporting product, growth, or marketing as a dedicated analyst. Typically, that experience is at a high-growth company with a well-defined product funnel. Often, candidates have an additional few years supporting other functions as a data analyst or in BI-, reporting-, or analytics-engineering roles. Experience with experimentation methodologies (A/B, MVT) is a plus
• Technical education: A bachelor’s degree in a technical or quantitative field (e.g., Analytics, Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, Finance, etc.). Bonus for a similar Master’s degree or a data science bootcamp
• Proficiency across analytics tools: Analytical SQL. Scripting in a notebook environment, using Python and Pandas. Intermediate statistics. Basic data science. Ability to quickly ramp up on GitHub, Snowflake, Looker, Amplitude, Segment, Optimizely, Airflow, DBT, and others
• Effective communicator across technical and business audiences. Curious; confident; open to questioning assumptions and being questioned. An incremental worker, able to balance vision and execution, and not easily discouraged

Responsibilities

• Be an excellent analyst: Uncover business questions. Develop rational hypotheses around these questions. Write research plans. Explore data in clean and raw forms. Soundly use statistics. Make clear visualizations. Uncover insights. Tell compelling data stories. Present to technical and executive audiences. Drive action and outcomes
• Support a product team: Collaborate with product managers, product leaders, designers, and engineers. Define, root cause, and forecast product metrics. Analyze products, customers, and business outcomes. Uncover what drives process success
• Use a growth toolkit: Think in terms of product activation, engagement, retention, and growth. Support iterative cycles of build, measure, and learn. Design, interpret and support product experiments and A/B tests. Educate partners on statistical validity
• Improve our analytics practice: Turn repetitive analyses into dashboards. Improve team processes. Build data pipelines and tables. Define requirements for better data. Improve data automation and analytics capabilities. Partner with data and analytics engineers

Benefits

You can work remotely anywhere in North America! You also have the option to work out of our San Francisco, Denver, Boston, or Toronto offices, once they reopen