The Environmental Law & Policy Center (ELPC) seeks to hire a full-time (40 hours/week) Geospatial Data Scientist intern for the summer of 2023. We are looking for a creative, enthusiastic PhD student/candidate who is passionate about finding ways to utilize GIS and data science to capture the hidden values in spatiotemporal datasets for environmental advocacy. The candidate selected for the position will work closely with the Data Science team.

LOCATION: This internship will ideally be based at ELPC's headquarters in Chicago, IL with flexibility to work remotely in the United States.

DURATION: Summer 2023, exact dates flexible with the possibility to extend depending on current projects.

INTERNSHIP REMUNERATION: This is a paid internship with an hourly rate of $25.00.

About ELPC:

The Environmental Law & Policy Center is the Midwest's leading environmental legal advocacy organization. We drive transformational policy changes with national impacts. We show that environmental progress and economic development can be achieved together by putting sustainability principles into practice. We advance climate solutions effectively by accelerating clean renewable energy alternatives to conventional power plants and advancing clean transportation solutions. We protect the Great Lakes and defend the Midwest's wild and natural places, and we fight for safe, clean water and healthy clean air for all. We combine effective public interest litigation with strategic policy advocacy, sound science, and economic analysis. ELPC produces strong results for the environment in the courtrooms, boardrooms, and legislative hearing rooms across the pivotal Midwest states and in Washington D.C.

Responsibilities:

• Conduct a literature review to assess the current state of knowledge and summarize it for use in relevant projects
• Exploration, collection, cleaning, and quality control of environmental, remote sensing and geospatial datasets for our projects
• Discover spatiotemporal dynamics and variability by domain knowledge integration in geospatial analysis, ML/AI modeling frameworks and statistical analysis
• Visualization and mapping of the results for public use in a manner that is clear and understandable
• Deliver well researched and organized reports with findings from the analysis

Qualifications:

• Must be enrolled in a PhD program and have completed coursework in a relevant field such as Agricultural Engineering, Environmental Engineering, Geography, Geology or other highly quantitative discipline
• Excellent research and writing skills
• Demonstrated interest in and commitment to public interest and environmental causes
• Outstanding analytical reasoning and problem-solving skills
• Demonstrated experience in processing remote sensing and large geospatial data
• Proficient in R or Python for complex data retrieval, mining, analysis, querying, and manipulation
• Demonstrated experience working with Google Earth Engine (JAVA/Python API)
• Proficiency in geoprocessing with GIS software such as ArcGIS, QGIS as well as coding skills with libraries such as Python Geopandas, GDAL etc.
• Solid understanding of AI/ML algorithm fundamentals, application, and tuning
• Data visualization skills in Python or R and dashboard tools such as Tableau/Power BI

Application Process:

We invite you to apply online and address your cover letter to Dr. Pouyan Hatami.

ELPC's EEO Statement:

The Environmental Law & Policy Center is committed to diversity, equity and inclusion in the workplace and provides consideration for an employment relationship without regard to race, color, religion, sex, sexual orientation, gender expression, gender identity, genetic predisposition, national origin, ethnicity, disability, veteran status, or any other characteristic protected by federal, state or local law.

If you are interested in any of our open positions but are unable to apply online due to a disability, please email us at gcronin@elpc.org with a reference to the specific job(s) you are interested in, and we will be happy to assist you.

Powered by JazzHR

i7opstXGxI