CX Business Intelligence Analyst

At Gusto, we're on a mission to grow the small business economy. We handle the hard stuff — payroll, health insurance, 401(k)s, and HR — so owners can focus on their craft and their customers. With teams in Denver, San Francisco, and New York, we support more than 500,000 small businesses nationwide and are building a workplace that reflects the people we serve.

All full-time employees receive competitive base pay, benefits, and equity (RSUs) — because everyone who helps build Gusto should share in its success. Offer amounts are determined by role, level, and location. Learn more about our Total Rewards philosophy.

AI is a fundamental part of how work gets done at Gusto. We expect all team members to actively engage with AI tools relevant to their role and grow their fluency as the technology evolves. AI experience requirements vary by role and will be assessed during the interview process.

Gusto's Customer Experience team is changing how we serve small businesses: new service models, a telephony platform migration, and the data infrastructure to support both. We are hiring a Business Intelligence Analyst to own the data layer that makes this work.

You will build the pipelines, models, and dashboards that make CX data trustworthy and self-serve, then use that foundation to answer causal questions about what actually moves customer outcomes. The strongest candidates pair real coding and statistical depth with the judgment to know which question is worth answering.

CX Data and Insights is the analytical backbone of Gusto's Customer Experience organization. We define the metrics CX leaders run the business on, and we produce the analysis that shapes operational roadmap decisions.

• Lead: Own ambiguous problems, design analysis and measurement frameworks, and introduce policies and practices by which data integrity is monitored and enforced within your domain.

• Execution: Deliver multiple high-impact projects, balancing trade-offs to maximize business value, and maintain clear expectations of deliverables and timelines.

• Strategic Partnership: Partner with CX leaders, cross-function data-science teams, tool developers (i.e. Salesforce), and data engineering to align on strategy.

• Analytical Rigor: Apply advanced statistical methods and AI-driven anomaly detection to proactively uncover opportunities, diagnose performance issues, and shape CX strategy, separating signal from noise. Navigate messy, conflicting data sources to establish reliable sources of truth. Use AI to accelerate hypothesis generation, code drafting, cross-source reconciliation, validation, and build agents to automate repetitive tasks.

• Develop and scale reporting: define DBT and Snowflake data pipeline requirements for evolving CX data sources, and build and maintain monitoring systems and streamlit dashboards for day-to-day operation and self-serve insights.

• Independence: Work with minimal guidance to prioritize, create, and deliver data projects, proactively resolving conflicts or misalignment across stakeholders.

• Scale the Craft: Up-level the team’s best practices in data modeling and schema design, expand our toolsets (e.g., Databricks for AI-augmented modeling and anomaly detection) where they accelerate CX outcomes, drive improvements in data quality, rigor, and adoption of better data capabilities, and mentor other data practitioners.

• Communication: