Customer Success Intelligence Analyst

Your Responsibilities
As a Customer Success Intelligence Analyst, you will help turn customer, dealer, and product data into insights that inform decisions across the business, including Customer Success, Product Engineering, and dealer-support teams. Working with the CS Intelligence product lead and stakeholders across the functions, you will take questions from initial scoping through analysis and delivery to build a repeatable Intelligence capabilities the organization can rely on.
Clarify the business question and the decision it should inform, and the analysis needed.
Analyze customer, dealer, product, and support data to identify and explain where customers encounter friction.
Build clear reports, visualizations, and summaries that connect findings to the evidence.
Validate data quality, definitions, and conclusions with subject-matter experts and technical partners, clearly communicating limitations and data gaps.
Manage analytical requests, communicate progress, and document recurring analyses so they can be reproduced or developed into scalable workflows.

What Skills You Need
Experience analyzing data to answer business questions and produce useful reports.
Strong data visualization and storytelling skills, with the ability to build clear dashboards, charts, and narratives that connect findings to customer needs and business decisions.
Comfort working through open-ended questions and incomplete or inconsistent data.
Ability to organize multiple requests, clarify priorities, and deliver agreed work.
Experience of knowledge graphs, including navigating connected data, and identifying relationships.
Proficiency with data-querying, analysis, or reporting tools. Examples may include Python, SQL, spreadsheets, and visualization tools.
Hands-on experience building AI skills, tools, workflows, and working with agentic coding tools such as Claude Code, Codex, and Github Copilot with the ability to orchestrate them effectively and verify the output.

What Makes You Stand Out
Knowledge of agricultural equipment, precision agriculture, or dealer and customer-support operations.
Experience navigating knowledge graphs or other connected-data models and using them for relationship matching, for example linking customers, dealers, machines, support cases, and product issues.
A hypothesis driven approach to answering questions, testing assumptions against available data, and developing clear, evidence-backed recommendations.

Education
Bachelor’s degree or equivalent relevant work experience.