Customer Success Analyst

Heartflow•Rohnert Park, CA

2d•$135,000 - $170,000•Hybrid

About The Position

Heartflow is seeking a Customer Success Analyst to join its Strategic Analytics team and provide analytical support to its Customer Success and Support organizations. The role owns data, models, and insights that help leaders make decisions about staffing, priorities, and operational improvements. The analyst will build capacity and headcount models, analyze support ticket data for themes and root causes, track customer health and adoption across sites, and deliver dashboards and analyses for leadership. The role 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 in its analytics work. The analyst will apply AI tools to accelerate SQL and Python development, classify and summarize unstructured ticket data, and help build automated, AI-assisted workflows for Customer Success operations. The position also requires following Heartflow data handling policies and applying safeguards to customer- or patient-related information encountered in support data. Heartflow is a medical technology company focused on the diagnosis and management of coronary artery disease. Its platform includes AI-driven, non-invasive products used by hospitals, imaging centers, and physician practices. The position is listed with a salary range of $135,000–$170,000 plus cash bonus. Heartflow is an Equal Opportunity Employer.

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.
Proven track record building capacity or headcount models and support ticket analytics used to inform staffing and operational decisions.
Advanced SQL skills and experience with a cloud data warehouse such as Amazon Redshift or similar, including complex joins, window functions, and deduplication logic.
Strong experience building dashboards in Tableau or a comparable BI tool, with decision-oriented visual design.
Deep working knowledge of Salesforce Service Cloud and Sales Cloud, including case and account data models, reports and dashboards, and data extraction for analysis.
Regular, demonstrated use of AI tools to accelerate analysis, write code, and process unstructured text; familiarity with prompt design, semantic models, LLM-based classification, and validating AI-generated outputs.
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 narratives for operational teams and senior leadership.
Self-directed, detail-oriented, comfortable with ambiguity, able to define metrics carefully, and willing to challenge conclusions that are not supported by data.

Nice To Haves

SOQL experience.
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 Customer Success and Support capacity models linking 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 of churn or declining engagement; work with CS leaders to prioritize proactive outreach.
Measure onboarding performance and the ramp of newly launched sites, identifying customer obstacles and factors that drive 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.
Partner with Sales Operations and Salesforce administrators to improve case and account data structures, ticket categorization taxonomy, 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 output accuracy and consistency.
Lead cross-functional deep-dive analyses by framing problems, selecting appropriate methods, and presenting findings to stakeholders at all levels.
Follow Heartflow data handling policies and apply appropriate safeguards to customer- or patient-related information encountered in support data.