Summer 2026 Corporate Internship Program

Albemarle Corporation (NYSE: ALB) leads the world in transforming essential resources into critical ingredients for mobility, energy, connectivity, and health. Our highly experienced and collaborative global team of operators, scientists and engineers work with deep technological resources in world-class facilities to pioneer new ways to move, power, connect and protect with people and planet in mind. We are a leading global provider of bromine, lithium, and highly specialized solutions that responsibly advance a more resilient world.

Albemarle is seeking rising sophomores and juniors to join our Summer 2026 Internship Program. The ideal candidate would be available to work full-time for 12 weeks from May 18th - August 7th at any one of our sites.

Please see the following available locations for corporate internships:

• Charlotte, NC

We are currently seeking interns to support the following functions:

• Data Science

QUALIFICATIONS

• Strong written and verbal communications skills
• Must be able to commit to a full-time schedule (40 hrs/week)
• Prior internship experience is a plus.

EDUCATION

• Seeking sophomore or junior level candidates (any graduation date between Dec 2026 to Dec 2028)
• Pursuing a bachelor’s degree in Data Science, Computer Science, Business Administration, or a business related field.
• Desired Cumulative GPA 3.0 or above on a 4.0 scale
• Experience in Power BI, Tableau, or Python a plus

JOB RESPONSIBILITIES

Job Responsibilities for a Data Analytics Intern include one or more of the following:

• Designed and published a Power BI dashboard displaying service health, ticket volumes, SLA performance, backlogs, category drivers, and trend alerts for monthly HR reviews
• Design and delivery of an end‑to‑end AskHR Intelligence workflow to standardize ticket classification, enrich case data, and improve service insights for HR leadership
• Implement a data quality controls—completeness validation, duplicate detection, and value‑range checks—to ensure reliability of HR operational analytics.
• Develop a baseline rule‑based ticket classifier using keyword logic and taxonomy mapping to standardize routing and reduce manual classification work.
• Built a comprehensive data dictionary outlining ticket fields, Workday enrichment attributes, and data lineage to ensure consistent enterprise‑wide usage.