Customer Success Analyst

Heartflow•San Francisco, CA

1d•Hybrid

About The Position

Heartflow is seeking a Customer Success Analyst to join its Strategic Analytics team and provide analytical support to the Customer Success and Support organizations. The role owns the data, models, and insights that help leaders make decisions about staffing, priorities, and operational improvements. The analyst will develop capacity and headcount models, analyze support-ticket data for themes and root causes, track customer health and adoption across Heartflow’s site base, and deliver dashboards and analyses for leadership. The position works cross-functionally with Customer Success, Support, Sales Operations, Finance, and Product, translating operational questions into rigorous analysis and practical recommendations. The team uses AI-forward analytics. The analyst will apply AI tools to accelerate SQL and Python work, classify and summarize unstructured ticket data, and help develop automated, AI-assisted workflows for Customer Success. The role also includes following Heartflow data-handling policies and applying safeguards to customer- or patient-related information encountered in support data.

Requirements

Bachelor’s degree in a quantitative or analytical field such as Business Analytics, Economics, Statistics, Engineering, or Computer Science, or equivalent practical experience.
3–5+ years of experience in analytics, including at least 2 years supporting Customer Success, Support, or Customer Operations teams.
Hands-on experience in Customer Success or Support Operations, including capacity and workforce planning and deriving insights from support-ticket data.
Advanced SQL skills and experience with a cloud data warehouse such as Amazon Redshift, including complex joins, window functions, and deduplication logic.
Strong experience building dashboards in Tableau or a comparable BI tool, with clear, decision-oriented design.
Deep working knowledge of Salesforce Service Cloud and Sales Cloud, including case and account data models, reports and dashboards, and extracting data for analysis.
Demonstrated, regular use of AI tools such as Claude, ChatGPT, or Copilot to accelerate analysis, write code, and process unstructured text.
Working proficiency in Python, such as pandas, for data wrangling, automation, and analysis.
Strong Excel and modeling skills, including scenario-based capacity and demand forecasting.
Ability to communicate complex analysis as concise, compelling stories for operational teams and senior leadership.
Self-directed, detail-oriented, and comfortable with ambiguity; able to define metrics carefully and challenge conclusions unsupported by data.
Proven track record building capacity or headcount models and support-ticket analytics used to inform staffing and operational decisions.

Nice To Haves

SOQL experience.
Familiarity with prompt design, semantic models, LLM-based classification, and validating AI-generated outputs.
Experience with text analytics or NLP techniques.
Experience in medical device, healthcare technology, or B2B SaaS environments serving hospital or health system customers.
Experience with customer success platforms such as Gainsight or ChurnZero.
Experience with customer survey or NPS programs.

Responsibilities

Build and maintain capacity models for Customer Success and Support, connecting case volume, site growth, ticket demand, and handle time to staffing needs; support annual planning and in-year headcount decisions.
Analyze Salesforce case data to identify volume drivers, recurring issues, root causes, and trends by site, product, and issue type, and recommend actions to Support, Product, and Operations.
Define and track operational KPIs, including ticket volume, first response time, time to resolution, backlog, SLA attainment, escalation rates, and workload distribution.
Develop and refine customer health scoring, adoption and utilization tracking, and early-warning indicators for churn or declining engagement; partner with Customer Success leaders on proactive outreach.
Measure onboarding performance and the ramp of newly launched sites, identifying where customers stall and what drives faster adoption.
Build and maintain Tableau dashboards and recurring reports for Customer Success and executive audiences, explaining what changed, why, and what actions to take.
Work with Sales Operations and Salesforce administrators to improve case and account data structures, ticket categorization, and data quality.
Use LLMs and AI tools to classify, cluster, and summarize ticket text and customer feedback; automate recurring reporting and data pipelines; and evaluate AI outputs for accuracy and consistency.
Lead deep-dive analyses on cross-functional questions, select appropriate analytical methods, and present findings to stakeholders at all levels.
Follow Heartflow data-handling policies and safeguards for customer- or patient-related information encountered in support data.