Temp Data Scientist, EnviroLab — Environmental Analytics

UNKNOWN; Chapel Hill (NC); Hybrid; USD 60,000 - 90,000; Full time

Benefits offered by this job

Hybrid work arrangement

Professional training opportunities

Discounts at retailers and restaurants

Job summary

University of North Carolina at Chapel Hill houses the Data-Driven EnviroLab (DDL) at the Institute for the Environment. The Research Specialist/Data Analyst will support environmental, climate, energy, and sustainability research using R and Python to manage diverse datasets and produce accessible data products.

The role offers a hybrid work arrangement and opportunities to contribute to dashboards, policy-relevant analytics, and scholarly outputs, collaborating across data science, climate

Qualifications

• Bachelor’s degree in a discipline related to the assignment.
• Strong programming in R or Python with large/complex datasets.
• Experience with quantitative analysis or geospatial analysis.
• Experience with research data tools/workflows (GitHub, APIs, web scraping, databases).
• Ability to communicate technical findings in an interdisciplinary team.

Responsibilities

• Develop and maintain research datasets by integrating administrative, web, geospatial, policy, and other data sources.
• Build and maintain data pipelines using APIs, web scraping, automated collection, cleaning, classification, and validation.
• Conduct quantitative, statistical, and geospatial analyses to study environmental and policy questions.
• Create dashboards, visualizations, and data products for researchers, policymakers, and the public.
• Contribute to research reports, publications, and presentations by the interdisciplinary team.

Skills

R programming

Python

Data cleaning

Data visualization

Education

Bachelor�s degree in a related field

Tools

Git/GitHub

APIs

Web scraping

Databases

Job description

University of North Carolina at Chapel Hill houses the Data-Driven EnviroLab (DDL) at the Institute for the Environment. The Research Specialist/Data Analyst will support environmental, climate, energy, and sustainability research using R and Python to manage diverse datasets and produce accessible data products.

The role offers a hybrid work arrangement and opportunities to contribute to dashboards, policy-relevant analytics, and scholarly outputs, collaborating across data science, climate