Senior Data Analyst, Customer Operations
San Diego, California, United StatesAll locationsSan Diego, California, United StatesSan Francisco, California, United StatesOttawa, Ontario, CanadaPhoenix, Arizona, United StatesToronto, Ontario, CanadaLos Angeles, California, United StatesDenver, Colorado, United StatesSalt Lake City, Utah, United StatesAtlanta, Georgia, United StatesChicago, Illinois, United StatesHouston, Texas, United StatesPortland, Oregon, United StatesNew York City, New York, United StatesVancouver, British Columbia, CanadaWashington, D.C., Washington, D.C., United StatesSacramento, California, United StatesJacksonville, Florida, United StatesSeattle, Washington, United StatesMexico City, MexicoAustin, Texas, United States On-site
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About the role
As the first Senior Data Analyst embedded in Customer Operations you will have the unique opportunity to build the CS Analytics function and own analytics and operational insights for the department. You will partner closely with Customer Operations leadership & team, Product, Finance (RevOps), and Data Engineering to build trusted reporting, improve operational rhythms, and drive measurable outcomes across retention, expansion, customer health, and support efficiency.
What you'll bring
- You are a deeply analytical thinker who is curious and loves to solve problems.
- You are comfortable operating in a fast-moving environment with evolving priorities.
- You combine strong technical skills with an operator’s mindset and can communicate clearly with both technical and non-technical partners.
- 4+ years of experience in analytics, business operations, or business intelligence roles
- Strong SQL skills and experience working with analytical datasets and BI tools (Looker, Tableau, etc.), with an emphasis on performance, usability, and metric governance.
- Comfortable working within an existing Databricks environment, reading gold-layer schemas, running queries, and working with Data Engineering to understand what data is available and how to use it.
- Experience with Python (or similar) for analysis, forecasting, and modeling.
- A track record of building retention, churn, renewal risk, forecasting, or related analyses and translating outputs into business action.
- A strong foundation in statistics and experimental thinking, including hypothesis testing and measurement design.
- Strong communication skills, with the ability to influence stakeholders across technical and non-technical teams.
- Comfort working independently in an environment with evolving priorities.
- Experience with customer health scoring, churn modeling, retention and expansion analytics, or lifecycle analytics.