PhD LCA Data & Sustainability Intern

Proctor & Gamble; Mason (OH); On-site; USD 68,000 - 97,000; Part time

Benefits offered by this job

Meaningful work from Day 1

Mentorship and learning

Visible business impact

Collaborative environment

Job summary

Procter & Gamble is offering a 12-week PhD internship in Mason to build the data foundation for scaleable life cycle assessment in Beauty Care. You will develop and organize LCI data, turning diverse sources into model-ready datasets to enable sustainability insights and climate goal alignment.

The role emphasizes analytical problem solving, data management, and collaboration with multidisciplinary teams, with on-site work 4–5 days a week in Mason.

Qualifications

• Pursuing a PhD in a field related to life cycle assessment.
• Understanding cradle-to-grave LCA and data inventories.
• Experience organizing, cleaning, and harmonizing structured/unstructured data.
• Ability to work with multidisciplinary teams.
• Available for a 12-week internship May/early June–August 2027, onsite in Mason.

Responsibilities

• Identify and fill LCI data gaps, documenting assumptions and data quality.
• Organize unstructured cosmetic-industry LCI data into standardized formats for scalable LCAs.
• Develop methods for cleaning, harmonizing, versioning, and maintaining data.
• Test structured data in Beauty Care products for scalability.
• Suggest data-transfer improvements to support future automation.
• Work with data covering product formulation, raw materials, packaging, manufacturing, distribution, and consumer use.

Skills

Analytical

Data wrangling

Communication

Collaboration

Documentation

Education

PhD in Environmental Engineering

PhD in Chemical Engineering

PhD in Industrial Ecology

PhD in Sustainability Science

PhD in Data Science

Tools

Python

Databricks

SQL

Job description

Procter & Gamble is offering a 12-week PhD internship in Mason to build the data foundation for scaleable life cycle assessment in Beauty Care. You will develop and organize LCI data, turning diverse sources into model-ready datasets to enable sustainability insights and climate goal alignment.

The role emphasizes analytical problem solving, data management, and collaboration with multidisciplinary teams, with on-site work 4–5 days a week in Mason.