# Customer Success Performance Insight Analyst

**Company:** [Justworks](https://hotfix.jobs/companies/justworks)
**Location:** New York, NY
**Role:** Data Analytics
**Experience:** 3+ years
**Skills:** SQL, Data Pipelines, Data Modeling, Data Governance, Tableau, Looker, Sigma, LLMs, Prompt Engineering, Conversation Analytics, Rippit, Maestroqa, Nps, Dashboarding, Data Quality
**Posted:** 2026-09-11

> Build scalable customer success analytics systems, dashboards, data pipelines, and AI-driven QA workflows. The role requires advanced SQL, strong data modeling and governance skills, 3–5+ years of relevant experience, and the ability to translate complex analyses into operational decisions.

## Job Description

## Responsibilities

### Data Architecture & Systems
- Design and build scalable reporting frameworks and data pipelines for self-service insights across customer success operations and cross-functional teams.
- Own data strategy and architecture for customer experience operations, including metric definitions, data models, and governance standards.
- Architect dashboards and data exports covering customer health, agent performance, and operational efficiency across multiple systems.
- Distinguish process issues from structural problems and determine when to optimize workflows versus redesign systems.

### Analytics & Insights
- Analyze complex datasets to identify behavioral patterns, performance drivers, root causes, and operational improvement opportunities.
- Use conversation analytics, transactional data, and customer interaction data to report on revenue-impacting and experience-driving topics.
- Conduct deep-dive analyses of performance, customer satisfaction trends, and operational health metrics; translate findings into recommendations.
- Define, instrument, and track KPIs for customer experience, agent performance, operational efficiency, and AI accuracy.
- Partner with leadership through data-driven storytelling and evidence-based insights.

### AI, Automation & Operations
- Design, train, and implement LLM prompts for QA automation, insight generation, and customer feedback synthesis.
- Evaluate AI-generated outputs for accuracy, clarity, and business impact; build feedback loops to improve AI systems.
- Identify and implement automation opportunities in QA, reporting, and customer feedback analysis.
- Maintain and optimize analytics platforms, dashboards, metrics, reporting pipelines, and data exports.
- Liaise with analytics platform providers to troubleshoot issues and maintain system reliability.
- Establish data quality, documentation, governance, and access standards across CX systems and reporting layers.
- Build knowledge systems, dashboards, runbooks, and documentation for human and AI consumption.
- Manage NPS outreach, including direct customer follow-up, and present targeted analyses to leadership.

### Collaboration
- Collaborate with Research and Voice of Customer teams to synthesize insights and identify customer experience improvements.
- Partner with Support, Enablement, Revenue Operations, Engineering, and Data & Analytics teams on tooling, data definitions, and infrastructure.
- Deliver recurring reporting and insights to leadership through dashboards, newsletters, and executive summaries.
- Translate customer success operations needs into data requirements.

## Requirements
- Advanced SQL proficiency, including complex and performant SQL for data exploration, validation, modeling, dashboards, and reporting.
- 3–5+ years of experience in data analytics, customer analytics, CX operations, quality assurance, or related roles focused on building scalable data systems and frameworks.
- Experience applying systems thinking to operations and designing scalable processes, data flows, or analytics infrastructure.
- Advanced experience designing and maintaining dashboards, reports, and data pipelines.
- Strong data fluency, including metric definition, data quality, documentation, and analytical validation.
- Experience analyzing large datasets and translating findings into actionable business recommendations.
- Experience with BI and analytics tools such as Tableau, Looker, or Sigma.
- Experience working with structured and unstructured data.
- Experience designing, training, or managing LLMs or similar AI models for evaluating customer interactions, transcripts, or agent outputs.
- Proficiency with QA platforms; Rippit or MaestroQA preferred.
- Strong troubleshooting, process optimization, communication, organization, and cross-functional influence skills.
- Ability to manage complex analytical workflows independently and collaboratively.
- High attention to detail and strong systems thinking.

## Nice-to-Haves
- Experience building or maintaining customer experience, support operations, or quality assurance analytics systems.
- Experience with conversation analytics, NPS programs, or Voice of Customer initiatives.

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