CX Intelligence Analyst — AI-Driven Data & Dashboards

Gusto, Inc.; Denver, New York (CO, NY); Hybrid; USD 111,000 - 139,000; Full time

Benefits offered by this job

Equity (RSUs)

Benefits and total rewards

Office presence in Denver

Job summary

Gusto is hiring a Business Intelligence Analyst to own the CX data layer, pipelines, data models, and dashboards that support CX decisions. You will work with CX leaders and cross-functional teams to deliver reliable data, enable causal analysis, and drive data-informed decisions.

Ideal candidates combine coding depth with statistical rigor and the judgment to pick impactful questions, while embracing AI-augmented modeling and governance across data products.

Qualifications

• 3+ years of experience in Data Analytics, Data Engineering, or Data Governance.
• Strong SQL and Python proficiency for large datasets.
• Solid data modeling, schema design, and data quality practices on cloud platforms like Snowflake.
• Experience building robust data reporting pipelines and ETL workflows.
• Experience designing or governing AI-assisted analytics outputs with validation standards.

Responsibilities

• Lead ambiguity in problems and design analysis frameworks.
• Execute multiple high-impact projects with clear deliverables and timelines.
• Partner with CX leaders, data-science teams, and data engineering to align on strategy.
• Apply statistical methods and AI-driven anomaly detection to improve CX outcomes.
• Define data pipeline requirements and build monitoring systems and dashboards.

Skills

SQL

Python

Data modeling

Communication

AI-driven analytics

Tools

Snowflake

DBT

Databricks

Salesforce

Job description

Gusto is hiring a Business Intelligence Analyst to own the CX data layer, pipelines, data models, and dashboards that support CX decisions. You will work with CX leaders and cross-functional teams to deliver reliable data, enable causal analysis, and drive data-informed decisions.

Ideal candidates combine coding depth with statistical rigor and the judgment to pick impactful questions, while embracing AI-augmented modeling and governance across data products.