Senior Customer Success Data Analyst
Seclore (company site, opens in a new tab)5–7 yrsMumbaiOn-siteDirect career pageEst. 14–22 LPA
Posted 20h ago
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Job description
Structured overview of role & requirements
About This Role
- Own and drive the Customer Success (CS) analytics strategy, including metric frameworks, customer health scoring, and churn prediction models to improve adoption, retention, and expansion.
- Design and integrate data from diverse sources (Salesforce, Statisfy, Freshdesk, product telemetry) to build unified CS dashboards and reporting for leadership and CSMs.
- Leverage predictive analytics and AI tools, including LLMs like Claude, to provide actionable insights, automate workflows, and support risk-weighted renewal forecasting.
Minimum Requirements
- 5-7 years in data analytics with 2-3 years specifically in customer success, revenue, or business operations analytics in B2B SaaS or enterprise software.
- Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, Engineering, or related quantitative field; master's degree is a plus.
- Advanced proficiency in SQL and Python for data wrangling and predictive modeling; expert-level skills in Power BI and Excel dashboard creation.
- Hands-on experience with Salesforce data and administering/configuring customer success platforms such as Statisfy, Gainsight, Totango, or ChurnZero.
Ideal Candidate Profile
- Experienced in building and operationalizing customer health scores and churn models that inform CS team actions and leadership decisions.
- Able to define and enforce data-quality and governance standards across multiple CRM and analytics platforms in a fast-evolving environment.
- Comfortable working cross-functionally with CS, Product, Engineering, Finance, and Sales leadership to influence strategies based on analytics and data storytelling.