Oferta compartida por Cristina
Data Scientist (Flexible work location)
YOUR POSITION WITH TNC
The Nature Conservancy’s North America Region Science team undertakes research in support of priority strategies, including natural climate solutions, renewable energy deployment, quantification of ecosystem services, and conservation prioritization exercises. The data scientist will conduct large-scale spatial analyses and modeling efforts to quantify and predict changes in land use, biodiversity, carbon storage, and other ecosystem services. The Data Scientist will work in a highly collaborative, driven, and multidisciplinary environment to address pressing conservation challenges. They will be involved in all aspects of research and will have the opportunity to lead projects and publish results as lead author. The Data Scientist will be supervised by the Director of Science for North America.
This location for this position is flexible.
ESSENTIAL FUNCTIONS
The Data Scientist works collaboratively to collect, process, and analyze data, build models, interpret and synthesize results, and draft and publish journal articles. They will work on a range of topics, addressing the most pressing and evolving needs to advance priority conservation strategies and emerging conservation threats and opportunities. Initial projects will address Natural Climate Solutions, wildfire resilience, energy siting, and conservation prioritization. Their work will focus largely on large-scale geospatial analyses using R and/or Python. The ideal candidate will be a savvy geospatial analyst, familiar with ArcGIS and comfortable leading GIS analyses; a competent statistician and experienced coder in R and Python; and a committed and passionate team player.
RESPONSIBILITIES AND SCOPE
Work collaboratively to develop tractable analytical solutions to conservation problems.
Acquisition, processing, quality control, and management of spatial and tabular data, coordinating data delivery to and from collaborators.
Conduct independent analyses of data, interpret results, and synthesize findings.
Collaboratively draft and edit reports and publications based on the data collected and analyzed.
MINIMUM QUALIFICATIONS
Master's Degree in ecology, natural resources, or geospatial science related field and at least 1 year of experience in a professional, scientific setting or equivalent combination of education and experience.
Experience conducting research to address conservation problems, including ability to quantify carbon storage and biodiversity outcomes.
Experience in all aspects of the scientific process:
Collecting, manipulating, analyzing and interpreting scientific data.
Reading, analyzing, and synthesizing scientific literature.
Communicate findings for stakeholders with varying degrees of scientific education.
Experience using GIS, e.g., ArcGIS or QGIS, to complete advanced geospatial analyses.
Experience using code-driven analytical tools, e.g., R or Python, to manipulate and analyze spatial and tabular data.
Experience with written and verbal communications skills.
DESIRED QUALIFICATIONS
PhD in natural resources or geospatial science related field and 1 year of experience or equivalent combination of education and experience.
Collaborative, detail-oriented person with the ability to stay organized and meet deadlines.
Ability to independently lead research projects.
Ability to think and work creatively, and to proactively identify and solve analytical and methodological problems.
Strong knowledge of computer technology and common software applications.
Ability to contribute to the development of R packages or other technology-based deliverables.
Experience with cloud based and distributed processing (e.g., AWS, Azure) addressing large scale data problems.
Experience in accessing data through API code interfaces
Experience working with remotely sensed data, land use and land cover change mapping, and image classification, using software packages such as Google Earth Engine, Microsoft Planetary Computer, ERDAS and ENVI.
Demonstrated ability to draft and publish scientific journal articles.
Demonstrated experience with large literature reviews, e.g., for the development of annotated bibliographies and/or databases.
Demonstrated ability to initiate projects and lead them to completion.
Multi-cultural or cross-cultural experience appreciated.
