About the Data-Driven EnviroLab
The Data-Driven EnviroLab (DDL) at UNC-Chapel Hill is a research laboratory with projects including measuring urban environmental performance, assessing sub-national and non-state climate action, and measuring co-benefits of renewable energy and energy efficiency. The DDL uses cutting-edge data analytics to develop solutions to the world’s environmental problems. Launched in 2015, the research group is an interdisciplinary collaboration of policy experts, data scientists, visual designers, and interactive programmers across UNC-Chapel Hill and Yale-NUS College, Singapore. Their work has been published in high-profile academic journals, including Nature and Nature Climate Change, and has been featured in popular media, including The Economics, The New York Times, The Atlantic, and Scientific American.
About the positions
The DDL is seeking two student research assistants to contribute to a range of projects aimed to bring quantitative rigor and analysis to environmental policymaking. Student research assistants contribute to all levels of work at the DDL, from research and writing to data analysis, visualization, and design. Research assistants will work collaboratively with full-time research staff, the faculty director, other students, and external partners all around the world. Research assistants receive training in data-driven approaches to environmental policy, which can involve statistical data analysis, quantitative research, and writing for policy audiences.
Positions are available beginning in Spring 2021 for part-time work, with the possibility of extension at least through the summer. During the academic year, students are expected to work an average of 10 hours per week but can work up to 19 hours per week. Pay starts at $15 per hour. The DDL is seeking to fill two roles, one student programmer/data scientist and one student research analyst.
The DDL is looking for students with data science skills who are interested in using statistics and programming to assist with a range of tasks, from statistical modeling to development of front-end data visualizations and graphics. In the past, they have developed interactive infographics, high-resolution maps, and data portals and dashboards.
- Ability to analyze and visualize data
- Background in statistical concepts as evidenced by previous work or coursework
- Ability to collect, manipulate, and clean data
- Familiarity with R
- Ability to communicate analytical findings, including at internal meetings and in public-facing communications (blogs, background papers, etc.)
- Ability to work with R tidyverse framework and write tidy code
- Ability to develop and optimize data scraping software
- Experience with statistical modeling
- Experience with computational methods commonly used in the social sciences (cluster analysis, PCA, etc.)
- Familiarity with natural language processing and text-based analytics (topic modeling, sentiment analysis, etc.)
- Experience with website maintenance (WordPress)
- Experience with literature review and synthesis
The DDL is looking for computer science students who are interested in practical programming experience to assist with a range of tasks, from big data mining to development of front-end data visualizations and graphics. In the past, programmers have helped build databases, scrape public data sources, and develop machine learning models.
- Experiences with working with large structured data and unstructured data (geospatial, weather, etc.)
- Experiences with statistical analysis, data visualization packages in R or Python
- Experiences with web scraping tools, packages, and methods in R or Python
- Possess excellent technical writing skills for documenting database structure and content
- Possess excellent communication skills, both written and verbal; be able to independently prepare correspondence and write/edit/produce reports
- Knowledge of the basics of GIS and remote sensing
- Work on open-source geospatial calculation tools utilizing GIS (QGIS or ArcGIS) in a Bash environment utilizing command-line tools (GFAL/OGR/GRASS)
- Experiences with geospatial data Python libraries (GDAL, rasterio, geopandas, Shapely, etc.)
- Development and maintenance of database tools written in open source languages (PostgreSQL, SQLite, etc.)
Send a resume, cover letter, and any other relevant materials (code samples, Github page, writing samples, etc.) to Brendan Mapes at firstname.lastname@example.org with the subject “DDL RA application.” Indicate in the body of the e-mail your availability to start and the specific position (data analyst or programmer) you are applying for.