There’s nothing more rewarding than knowing you’re making a difference every single day. Here at The Everglades Foundation, we are restoring one of the most important ecosystems on the planet, protecting the drinking water supply for over 8 million Floridians, helping small businesses thrive, guarding over 78 threatened and endangered species, and securing an iconic American landscape for future generations.
By joining The Everglades Foundation team, you’ll be diving into a whirlwind of scientific research, environmental policy, innovation, education, and stewardship. Whether you’re working from your desk, exploring Everglades National Park, or advocating in Washington D.C., you’ll be taking on the largest ecosystem restoration project in history.
JOB OPENING: Data Analyst / Statistician
The Everglades Foundation, a non-profit organization dedicated to the restoration of the Everglades, is looking for a graduate research associate to work on environmental water quality data analysis projects. The Everglades Foundation is a science-driven organization and as such, our policies and priorities are driven by our sound science.
This is a 6-month position located in our Palmetto Bay, Florida (Miami) office, starting in January 2020. The successful candidate will be expected to have advanced skills in statistics and data analysis and with basic knowledge of hydrology, environmental chemistry and water quality. Statistical hypothesis testing, geospatial analysis, and proficiency in working with datasets is critical for this position.
Responsibilities and Duties:
The primary responsibilities of the data analyst include:
- Compiling data from different sources related to hydrology and water quality in the Everglades;
- Processing monitored data (e.g. concerning water, soil, plants) and analyzing temporal and spatial changes in South Florida;
- Developing user friendly computer scripts and codes for routine water quality data analysis.
- Performing mathematical and computational analysis of water quality with respect to environmental regulations and restoration goals;
- Applying advanced statistical techniques and analytical capabilities to derive trends and correlations;
- Presenting results in technical reports and scientific articles.
Eligibility and Requirements:
Recent graduate students and post-graduate associates are eligible for this fix-term position. The position is open to any advanced graduate student) with strong skills and a proven track record in data analysis, quantitative analysis and statistics with background in hydrology, water quality, and environmental data analysis. A candidate with a PhD degree in applied statistics, data analysis and science, Soil and Water Sciences, or a closely related discipline We are especially looking for a candidate that:
- has strong analytical skills to solve technical problems with result-oriented objectives.
- possesses strong background in statistical data analysis (hypothesis testing, trend analysis, multi-linear regression).
- experienced in manipulating databases and working with numbers (must be proficient in Microsoft Excel, Microsoft Access, and at least one of R, Matlab, and Python).
- has knowledge of mapping and spatial analysis in ArcGIS.
- has excellent writing skills and experience in communicating results to scientists and engineers in one or more forms.
- is familiar with the ongoing Everglades ecosystem restoration efforts (highly recommended but not essential).
The Everglades Foundation offers a competitive salary and benefits. We have a dedicated team of seven scientists and engineers and offer an excellent working environment. The Research Associate will work closely with Drs. Naja and Khare. If you are interested in joining us (or have questions), send a pdf version of your cover letter and Resume/CV (statistical and programming skills to be clearly included) to email@example.com. Application deadline is December 15, 2019. Applications will be assessed periodically until a suitable candidate has been identified. Therefore, applicants are encouraged to apply as early as possible.