Senior Customer Success Data Analyst

Role Overview

The Senior Customer Success Data Analyst owns how Customer Success uses data to improve adoption, retention, drive expansion and decide where CSMs focus. The role involves designing the CS analytics strategy, metric framework, customer health score and churn-prediction approach, and acting as the analytics partner to the Head of CS Operations and CS leadership.

What You Will Do

The Senior Customer Success Data Analyst will own the CS analytics strategy, metric framework, customer health score and churn-prediction approach, and act as the analytics partner to the Head of CS Operations and CS leadership. The role involves designing the CS analytics roadmap, prioritizing work by impact on retention and growth, and presenting insights to CS leadership and contributing to board-level reporting.

Why It Might Be a Fit

The role requires a proven track record of building customer health scores or churn models end to end and getting them adopted by CS teams, advanced SQL and strong Python for data wrangling, statistical analysis and predictive modeling, and expert-level dashboard building in Power BI and Excel.

Requirements

• 5–7 years of experience in data analytics, with at least 2–3 years in customer success, revenue or business operations analytics, preferably in B2B SaaS or enterprise software.
• Bachelor’s degree in Statistics, Mathematics, Economics, Computer Science, Engineering or a related quantitative field; a master’s degree is a plus.
• Advanced SQL and strong Python for data wrangling, statistical analysis and predictive modeling (e.g. logistic regression, survival analysis).
• Expert-level dashboard building in Power BI and Excel.
• Deep experience with Salesforce (or a similar CRM) data — accounts, opportunities, renewals.
• Hands-on experience administering or configuring a customer success platform such as Statisfy, Gainsight, Totango or ChurnZero.
• Experience designing data models and working with data from multiple systems and raw sources.
• Strong command of SaaS and subscription metrics: ARR, GRR, NRR, churn, renewal rate, adoption.
• Advanced, hands-on AI user with experience applying LLMs such as Claude to analysis, coding, automation and documentation.
• A track record of influencing senior stakeholders and driving decisions with data and clear storytelling.
• A builder mindset and comfort creating structure, standards and processes where none exist yet.
• Excellent written and verbal communication in English.

Benefits

• Competitive salary
• Benefits package
• Opportunities for professional growth and development
• Collaborative and dynamic work environment

Tagged as: Data Analysis