Senior Research Data Support Analyst - Yale School of the Environment
Date posted
Mar. 4, 2024 11:00 am
Application deadline
Apr. 4, 2024 5:00 pm
Organization
Yale University
Location
- United States
Job description
Position Focus:
Join the Yale School of the Environment (YSE) and use your data and computational skills to help tackle important environmental and sustainability challenges, including climate change, biodiversity loss, and the energy transition.
Successful candidates will provide professional consultation and direct support to researchers engaged in data-intensive projects across the many disciplines in YSE. They will consult with and guide researchers on data pipelines and computational workflow, guiding and helping directly implement solutions. Solution may include data workflow design plans and protocols for maintenance and management of data sets through all phases of research; review progress and assure accuracy and compliance of data being acquired and stored; computational research support, which may range from suggesting to implementing approaches to helping streamline and improve coding efficiency.
Successful candidates will also provider mentorship to less experienced members of the team, and also work with and serve as a liaison between YSE researchers and Yale-wide computational support organizations including the Yale Center for Research Computing (YCRC), the library and statistics lab, Data intensive Social Science Center (DISSC), the Geospatial Data Research Center, and the Digital Humanities Lab. This position reports to the Sr. Associate Dean or Assistant Dean of Research for the YSE.
Individuals in this position are expected to have the necessary skills to help acquire data from various sources; cleaning, merging, and organizing complex data across multiple projects; improving coding efficiency; and creating data visualizations. Ideal candidates will have practical working experience organizing large data sets in a linux environment, often requiring parallel processing (e.g., dask, spark, dbt), and working in R, python, or SQL environment. YSE research projects may involve working with data set too large to load into RAM all at once; cloud services (i.e. AWS, Azure, and Google Cloud); columnar data types, coding collaboration solutions (e.g., GitHub). Successful candidates are expected to have experience with, or by ready to learn, data visualization; statistical methods, machine learning and AI-based methods; geospatial data management, image processing and computer vision; and text to data.