The Cadenasso Landscape and Urban Ecology Lab at UC Davis, Department of Plant Sciences, seeks a GIS Analyst to fill a Research Data Analyst position. The GIS Analyst will work on interdisciplinary projects focused on water use and vegetation in Sacramento, CA. Within this overarching goal, the GIS Analyst will be responsible for locating, curating and analyzing datasets of urban tree inventories; mapping vegetation, parcel, and socio-demographic data; maintaining all appropriate metadata; and contributing to the documentation of methods. A basic understanding of ecology and environmental science is desired so that the candidate can meaningfully engage with the research. The successful candidate should expect to work with a variety of data and data types, be comfortable with ESRI ArcGIS, and be willing to learn new tools and techniques.
The Analyst will work closely with the Principal Investigator (Cadenasso), a Post-Doctoral Researcher, and undergraduate employees and interns located at UC Davis, as well as with members of the larger collaborative team located throughout California. The successful applicant is expected to generate high quality mapping products for reports, publications, and presentations and, maintain and organize databases. They will also be expected to engage with collaborators, handle data sharing, and be able to articulate the goals of the research project to a wide range of audiences, including academic, public agency, and local community groups. The Analyst will be considered a full member of the Cadenasso Lab, and as such will be expected to be an active member of a vibrant intellectual community, preparing for and attending lab meetings and providing critical feedback to other projects occurring in the lab.
ÃfÂ¢Ã’ÂEURÃ’Â¢ BachelorÃfÂ¢Ã’ÂEURÃ’Â(tm)s or MasterÃfÂ¢Ã’ÂEURÃ’Â(tm)s degree in ecology, or related field, with strong GIS skills; Certificate in Geographic Information Systems desired.
ÃfÂ¢Ã’ÂEURÃ’Â¢ Experience using ESRI ArcGIS software suites, specifically the tools and functions within ArcGIS Online, ArcGIS Pro 2.5+, ArcMap 10.7+, Survey123 (online and desktop) & Collector for ArcGIS utilizing both tabular and geographic data creatively. Experience using & maintaining these software platforms on iPad and desktop connections is highly desired.
ÃfÂ¢Ã’ÂEURÃ’Â¢ Willingness to think about and use various spatial tools creatively.
ÃfÂ¢Ã’ÂEURÃ’Â¢ Familiarity with spatial statistics tools within ArcGIS.
ÃfÂ¢Ã’ÂEURÃ’Â¢ Strong data and file management skills.
ÃfÂ¢Ã’ÂEURÃ’Â¢ Familiarity with eCognition software a plus.
ÃfÂ¢Ã’ÂEURÃ’Â¢ Excellent written and oral communication skills; comfortable seeking data and information from other professionals by phone.
ÃfÂ¢Ã’ÂEURÃ’Â¢ Flexibility to work both as a team member and independently.
ÃfÂ¢Ã’ÂEURÃ’Â¢ Excited to work with diverse undergraduate interns and graduate students in the lab.
ÃfÂ¢Ã’ÂEURÃ’Â¢ Willingness to travel to Sacramento for project meetings.
Duration: This position is full time and the initial offer will be for one year with up to a 6 month extension based on performance. Start date is negotiable, but on or before 1 August 2020 is highly desirable. The position includes salary and benefits commensurate with experience and demonstrated accomplishments.
To apply: Please send a cover letter highlighting your relevant experience and expertise, what interests you about the position, and career goals. Include a CV and the names and addresses of 3 professional references that can be contacted. It may be helpful to review the Cadenasso Lab website to get a better idea of the type of research we do: email@example.com Email all materials as a single pdf file to Mary Cadenasso at MLCadenasso@ucdavis.edu, with ÃfÂ¢Ã’ÂEURÃ’ÂoeResearch Data AnalystÃfÂ¢Ã’ÂEURÃ’Â in the subject line. Applications will also need to be uploaded to the UC Davis HR site at: https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fhr.ucdavis.edu%2Fcareers&data=02%7C01%7Cmadeline.hennessey%40uconn.edu%7C2b900661188543da01f508d819b12124%7C17f1a87e2a254eaab9df9d439034b080%7C0%7C0%7C637287595840204204&sdata=v42V%2FrdbX91aNV4nuhlVrf3Ifr28F3xYbwUoZmZzMag%3D&reserved=0