Human Resources Data Scientist
Idaho National Laboratory
Job Overview
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Job Description
About the Human Resources Data Scientist Role
The Human Resources Data Scientist at Idaho National Laboratory serves as a strategic analytics partner to HR leadership, translating complex workforce data into clear, compelling insights that inform executive decision-making.
This role blends advanced data science capabilities with strong business acumen. It demands executive-level communication and a customer service mindset focused on HR stakeholders.
Key Responsibilities
- Design and maintain advanced analytics solutions for HR strategy.
- Perform complex analysis using structured and unstructured data sources.
- Extract, transform, and integrate data autonomously.
- Build executive-ready dashboards and visualizations using Power BI.
- Translate analytics findings into actionable insights for senior leadership.
- Partner with HR professionals to ensure business-aligned analytics.
- Present detailed findings to senior leaders and mentor junior colleagues.
- Utilize AI-enabled tools to enhance analytics workflows.
Minimum Qualifications
Bachelor's degree in Data Science (9+ years experience) or Master's degree (6+ years) for Level 4; higher experience requirements for Level 5.
Preferred Qualifications and Portfolio
Certifications in data science and experience in regulated environments such as government labs. A portfolio showcasing executive dashboards, data visualizations, or analytic tools is encouraged.
Additional Information
This role includes mentoring responsibilities, physical demands such as standing and lifting up to 25 pounds, and opportunities for relocation and excellent benefits. INL is an Equal Employment Opportunity employer.
Key skills/competency
Data Science, Analytics, Power BI, Executive Communication, Data Integration, Dashboarding, AI Tools, Workforce Planning, Mentorship, Business Acumen
How to Get Hired at Idaho National Laboratory
- Customize your resume: Emphasize data science and HR analytics experience.
- Highlight technical skills: Include Power BI and AI tool expertise.
- Prepare for leadership questions: Emphasize strategic insights.
- Showcase portfolio work: Provide executive dashboard samples.
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