AI Native HR Data Analyst
New
F
FortrexFood safety
United StatesFull-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- 3 or more years of related experience.
- Required Skills
- SQLMicrosoft Power BITableauMicrosoft Excel
Requirements
- Hold a bachelor’s degree in Human Resources, Business Analytics, Statistics, Data Science, or a related field.
- Be proficient with HRIS platforms and reporting or business intelligence tools such as Power BI, Tableau, Excel, and SQL.
- Use AI tools such as Claude, ChatGPT, or Copilot to support analysis, automate workflows, or accelerate reporting, with sound judgment to verify results.
- Interpret complex and sometimes messy datasets and turn findings into actionable insights.
- Design repeatable workflows instead of relying on recurring manual work.
- Understand HR metrics, workforce analytics, and compliance reporting.
- Communicate and present insights effectively to HR, Safety, and Compliance leadership.
- Manage multiple priorities and collaborate across teams.
- Maintain high attention to detail and commitment to data accuracy.
- Preferred: 3 or more years of related experience.
- Preferred: Experience designing AI-assisted or automated reporting workflows in HR or People Analytics.
- Preferred: Experience with predictive analytics and HR data modeling.
Responsibilities
- Use Claude and other AI tools to explore HRIS and workforce datasets, draft and refine queries, identify trends, and validate findings.
- Redesign repetitive manual reporting as automated, reusable workflows.
- Build systems that surface trends and anomalies in employee engagement, turnover, safety compliance, and workforce planning.
- Audit HR data and create automated checks for accuracy, consistency, and completeness.
- Design maintainable dashboards and reports using Power BI, Tableau, Excel, and AI-assisted tools.
- Partner with HR, Compliance, Safety, Operations, Finance, and IT to define reporting needs and align metrics.
- Translate ambiguous questions into concrete deliverables for stakeholders.
- Improve how data is collected, modeled, and communicated, and implement those improvements.
- Contribute to exploratory initiatives involving new metrics, predictive models, or AI tools.
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