Data Scientist and Data Manager

Key Skills

Batch Data Processing, Data Analytics, Data management, Data science techniques, Git, Large data sets, Machine learning techniques, Python Programming, R Programming, Statistics

Job Description

The Stanford Doerr School of Sustainability strives to create a future when humans and nature thrive in concert and in perpetuity. The school is made up of a three-part structure to drive global impact: Our academic departments and programs educate students and create new knowledge across areas of research that are crucial for advancing the long-term prosperity of the planet; Institutes bridge scholarship at Stanford and beyond, bringing multiple viewpoints to bear on urgent challenges; The Sustainability Accelerator drives new policy and technology solutions through a worldwide network of partners who work with our teams to develop solutions at a global scale. The school is dedicated to creating and supporting a diverse, equitable, and inclusive environment, and to creating solutions that benefit all people, particularly those most affected by environmental damage and climate change.

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Stanford Woods Institute for the Environment is working toward a future in which societies meet people’s needs for water, food, health, and other vital services while sustaining the planet. As the hub of interdisciplinary environment and sustainability research at Stanford University, the Woods Institute brings faculty, researchers, and students together in collaboration on environmental research. Their interdisciplinary work crosses sectors and disciplines, advancing solutions to the most critical, complex environmental and sustainability challenges.

The Natural Capital Project (NatCap) aims to create a future where people and nature thrive. We are working to build the scientific basis and broad institutional support for protecting Earth’s vital life-support services and the people and economies dependent upon them. With our global hub at Stanford University, we are a unique partnership and strategic collaboration among: the Stanford Woods Institute for the Environment, the Stanford Center for Conservation Biology, The Nature Conservancy, World Wildlife Fund, the Chinese Academy of Sciences, the Institute on the Environment at the University of Minnesota, and the Stockholm Resilience Centre. NatCap develops and applies new tools and approaches to better understand and integrate the full value of ecosystem services into decision-making. We are: (1) advancing science and developing software tools; (2) engaging with leaders to integrate understanding of nature’s benefits into decisions; and (3) mainstreaming our approach into policy, management, and finance.

The Natural Capital Project at Stanford University (NatCap) is seeking a Data Management Specialist/Data Scientist. The position will involve implementing and promoting NatCap-wide approaches to data management and data sharing in support of open science, as well as contributing to project-specific data management and data science needs.

Your responsibilities will include:

• Work across NatCap’s science, analyst, and software teams to identify data management and data science needs and implement solutions.
• Develop and maintain a NatCap data management plan and support staff in its adoption.
• Support team members in documenting data products and following metadata standards.
• Create, test, and modify software scripts and reproducible analytical workflows to support the NatCap team in producing high quality, discoverable, and reusable data. Such workflows will include data processing, creating figures, and implementing statistical models.
• Work with team members to develop and implement processes to promote data sharing and re-use.
• Maintain NatCap’s internal data catalog and support team members in contributing data to the catalog and in creating and storing documentation via human- and machine-readable metadata.
• Develop, maintain, and share geospatial datasets and other datasets.
• Serve as a resource for NatCap team members on best practices for data management.
• Work with team members and project partners to identify data needs, procure the best available data, and determine appropriate analysis methods.

* - The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned.

To be successful in this position, you will need:

• Bachelor's degree (such as data science, computer science, environmental science, biology, or related discipline) or a combination of education and relevant experience. 
• Basic knowledge and demonstrated experience using and applying analytical software, database management system software, database reporting software, database user interface and query software, and data mining software.
• Ability to collect data using a variety of methods, such as data mining and hardcopy or electronic documentation study, to improve or expand databases.
• Strong listening, verbal and written communication skills.
• Ability to manage multiple activities in a deadline-oriented environment; highly organized, flexible and rigorous attention to detail.
• Ability to use logic to calculate data; efficiently construct a database or scrutinize the form of a question.
• Ability to work with data of varying levels of quality and validity.
• Demonstrated ability to produce data in a clear and understandable manner meeting user requirement.
• Ability to work effectively with multiple internal and external customers.

In addition, our preferred skills and experience include:

• Advanced degree in data science, environmental science, or a related discipline, and/or at least four years of related experience.
• Strong analytical skills, including experience with research approaches and quantitative modeling.
• Fluency in Python and/or R, or fluency in another scripting language and a willingness to learn Python
• Experience with geospatial data and spatial analysis.
• Demonstrated ability to work both independently and as part of a team on multiple concurrent projects. Must be able to identify priorities and maintain awareness of multiple deadlines.
• To be independent, proactive, and have initiative.
• Experience using GIS software and spatial analysis in support of conservation, natural resources management, or ecosystem services assessment.
• Familiarity with the principles of open science and open source software.
• Experience using Python or R in a scientific context.
• Experience applying machine learning to satellite imagery or other geospatial data sets
• Experience collaborating on projects using a distributed version control system such as Git or Mercurial.
• Experience developing performant, interactive visualizations of large-scale geospatial data
• Interest in or experience with linux systems administration