Data Intelligence Analyst/Product Data Analyst — Moline, IL

Role Overview:

The Customer Success Intelligence Analyst will analyze customer, dealer, product, and support data to generate actionable business insights. The role focuses on using data to identify customer challenges, validate business assumptions through hypothesis-driven analysis, and provide evidence-based recommendations to improve customer experience, product performance, and dealer support.

Key Responsibilities

• Analyze customer, dealer, product, and support data to identify trends, patterns, and customer pain points.

• Develop and test hypotheses using data to validate assumptions and support business decisions.

• Create dashboards, reports, charts, and visualizations to communicate analytical findings.

• Use SQL, Python, Excel, and other analytical tools to extract and interpret data.

• Work with Customer Success, Product Engineering, and dealer-support teams to understand business requirements.

• Validate data quality, identify data gaps, and ensure accurate reporting.

• Explore connected data and knowledge graphs to identify relationships between customers, dealers, machines, and support cases.

• Leverage AI tools and agentic coding assistants to automate workflows and improve analytical efficiency.

Must-Have Skills

• Strong data analysis and problem-solving skills.

• Hypothesis-driven analysis – ability to test assumptions and support conclusions with data.

• Proficiency in SQL, Python, Excel, or similar data-querying tools.

• Data visualization, dashboard development, and storytelling.

• Experience with knowledge graphs or connected-data models.

• Hands-on experience using AI tools, building AI workflows, and agentic coding tools such as Claude Code, Codex, and GitHub Copilot.

• Ability to work with incomplete data and translate business questions into actionable insights.

Preferred Background

• Agricultural equipment or precision agriculture industry experience.

• Automotive industry experience.

• Digital product or customer-facing technology experience.

• Dealer support, customer success, or product analytics experience.

What the Hiring Manager Is Looking For

• Candidates who can take a business hypothesis, analyze relevant data, and determine whether the evidence supports it.

• Strong analytical thinking and the ability to communicate findings clearly.

• Practical experience using AI tools and agentic coding assistants.

• Candidates from agriculture, automotive, or digital product backgrounds.

Education

Bachelor's degree or equivalent relevant work experience.

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• Data Analysis: Strong experience analyzing customer, dealer, product, and support data to generate business insights.

• Hypothesis-Driven Analysis: Ability to develop hypotheses, test assumptions using data, validate findings, and provide evidence-based recommendations.

• SQL / Python / Excel: Proficiency in querying, analyzing, and interpreting data using SQL, Python, spreadsheets, or similar tools.

• Data Visualization: Experience building dashboards, reports, charts, and presenting analytical findings through clear data storytelling.

• Knowledge Graphs: Experience working with knowledge graphs or connected-data models to identify relationships across datasets.

• AI & Agentic Tools: Hands-on experience building AI tools, skills, and workflows using Claude Code, Codex, and GitHub Copilot.

• Business Communication: Ability to translate business questions into analytical requirements and communicate findings to stakeholders.

• Data Quality: Experience validating data accuracy, identifying gaps, and working with incomplete or inconsistent datasets.

Preferred Industry Background

• Agriculture / Precision Agriculture

• Automotive

• Digital Products / Technology