Description
Chesapeake Conservancy, a nonprofit organization based in Annapolis, Maryland is seeking a Geospatial Data Scientist with experience leveraging machine learning and large and complex data sets in the environmental world.
ABOUT THE CONSERVANCY
Chesapeake Conservancy is a non-profit organization based in Annapolis, Maryland, dedicated to ensuring a healthier Chesapeake Bay watershed where fish and wildlife thrive, with healthy waters and abundant forests, wetlands, shorelines, and open spaces. With the human population in the Chesapeake watershed approaching 18 million and growing and tens of thousands of acres of open space vanishing each year, the Conservancy works to connect people with the Chesapeake’s wildlife and history; conserve landscapes and rivers; and restore the region’s natural resources. The Conservancy works in close partnership with the National Park Service Chesapeake Bay Office, the United States Fish and Wildlife Service, as well as other federal, state and local agencies, private foundations, and corporations to advance conservation.
Within the Conservancy, the Conservation Innovation Center (CIC) group has become a globally recognized leader in producing data, analyses, and web applications to advance precision conservation and restoration. We partner with industry-leading organizations like Microsoft and Esri to help define the next generation of environmental data and work with partners on the ground to make sure it is useful. The CIC has recognized the potential of machine learning to dramatically improve the analysis of large and complex datasets to improve environmental decision making.
POSITION DESCRIPTION
The Geospatial Data Scientist, working within the CIC, will be responsible for the development and management of a variety of pilot projects both inside and outside the Chesapeake Bay watershed that demonstrate the role that AI and “big data” can play in environmental decision making. The successful candidate will have a unique opportunity to build a data science program within the CIC that works to address global challenges while getting to work at the cutting edge of data science and collaborating with other leading organizations.
Reporting directly to the Director of Conservation Technology, the successful candidate for this position will be involved in all aspects of projects from scoping, data evaluation, and project execution. This position will take the lead on creating a portfolio of projects leveraging machine learning and will work with the CIC’s team to identify opportunities to improve existing workflows. Experience with environmental issues, including water quality and quantity management, ecosystem and habitat modeling, and land management is highly desired.
Essential functions include:
1. Create machine learning solutions, including artificial intelligence, for a diverse set of problems.
2. Employ structured approaches to leveraging large data sets to uncover new insights.
3. Work closely with the team within the CIC to incorporate their expertise into new data science solutions that improve workflows and outcomes.
4. Drive acquisition of new data sources as needed with governance on license, terms of use, compliance, quality, and high availability.
5. Represent the CIC’s capabilities and product offerings to internal and external audiences, both technical and non-technical, at conferences and meetings.
6. Overseeing and collaborating with team members as well as other project managers. Candidates must be able to work within the CIC’s structure to add additional capabilities. This includes working with peers and supervisors in problem solving, and providing constructive feedback on ideas and problems. The CIC team is a highly collaborative and innovative group. Ideal candidates will participate in brainstorming and discussions.
7. Obtaining, organizing, and processing component datasets. The Geospatial Data Scientistwill be working with a variety of spatial data, including satellite and aerial imagery; LiDAR; national, state, and local vector data; and ecological models. Organization and attention to detail are key skills in working across projects with high volumes of complex data.
8. Working independently to solve problems and errors. Much of the CIC’s work involves finding unique, customized solutions to partners’ challenges. Errors and unknowns will be encountered. This position will be required to handle a range of technical challenges and to devise solutions based on available resources. While this position will be the only data scientist within the CIC, this position will work closely with partners with strong data science programs.
9. Compiling deliverables and writing grant reports. Project deliverables may include maps, memos, short or long reports, slide decks, datasets, or grant reports. Applicants should be able to write concisely and effectively, design impactful products, and communicate progress to funders.
Requirements
KEY QUALIFICATIONS
The Geospatial Data Scientist should be an organized, dependable, and goal-driven leader with a passion for the mission of the Chesapeake Conservancy – public access, conservation, and education and stewardship of the Bay and its resources. Candidates must be able to challenge conventions, to thrive independently as well as on a team in a relaxed, dynamic office culture, and to think creatively. Other essential skills include adaptability, independence in problem solving, strong oral and written communication, and an ability to teach others technical material.
Job Requirements:
• Master’s in a quantitative field. Ph.D. preferred.
• Experience in delivering insights and capabilities through data science, AI or machine learning techniques. E.g., neural networks for NLP, computer vision, etc., random forests and other supervised methods, clustering, PCA, etc.
• Experience with a numerical programming language such as Python/Numpy/Scipy, R, Matlab, or similar
• Familiarity with SQL or similar.
• Research or strong experience in computational aspects of one or more of the following, or highly related, areas preferred: Bayesian modeling, causal inference methods, finite mixture models, generalized linear models, joint modeling, nonlinear mixed models
• Comfort manipulating and analyzing complex, high-dimensionality from varying sources to solve difficult problems
• Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner
• Experience framing and participating in data-driven business decisions, including measuring and evaluating outcomes.
• Excellent oral and written communication skills.
• The ability to translate data science to non-technical people at all levels.
• Team player with proven ability to build trusted relationships.
• Demonstrated ability to work efficiently, prioritize workflow, and meet demanding deadlines.
Skills/Experience nice to have
• Experience with CNTK, Tensorflow, Keras
• Experience with cloud based architectures such as Azure or AWS