Scientific Data Manager

Overview

The Soil Health Institute (SHI), a non-profit organization created to safeguard and enhance the vitality and productivity of soil through scientific research and advancement, seeks to hire a full-time Scientific Data Manager. The Scientific Data Manager leads the organization, QA/QC, validation, and documentation of soil health and agronomic datasets to ensure accurate, accessible, and scientifically defensible data products that support SHI research and external partnerships.

This role will work closely with SHI scientists across projects to maintain access and information on existing SHI datasets and curate new datasets from ongoing sampling campaigns.

The Scientific Data Manager will be responsible for receiving soil, manure, plant tissue, greenhouse gas, water quality, and other data from partnering laboratories and scientists, performing QA/QC, providing high level data summaries, communicating the status of new and existing data to SHI scientists, and providing external partners access to curated datasets. Year one of the position will focus on receiving, validating, and sharing data with SHI scientists and external partners, as well as working with front end software developers and scientists to integrate SHI’s Postgres relational database into an online portal currently under construction, and enhancing the summary and synthesis of data currently held within SHI’s data infrastructure.

The selected individual will be supervised by Liz Rieke, PhD, Soil Microbiome Scientist and Program Director and as part of the SHI Data team, including field operations and research soil scientists. This position will work with SHI as a full-time employee. The initial position fills as a 12-month deliverable cycle with extension beyond 12 months based on satisfactory performance and Institute needs.

We seek a self-motivated, curious individual, with appropriate skillsets for building, curating, synthesizing, and communicating high quality data products for project-specific and Institutional purposes. Position start date is flexible but preferred by March 15, 2026.

• Receive data from commercial laboratories, perform QA/QC, submit sample reruns as necessary, push timely database updates and approve invoices from partnering laboratories
• Consistently communicate the status of newly collected and historical data to SHI scientists and external partners
• Collaborate with data operations specialist to merge measurement data with meta and management data
• Manage online code repository, VPN, cloud computing, and geospatial software accounts
• Develop and manage scientists’ access permissions to SHI data
• Streamline SHI scientists’ ability to access and analyze data by creating systems for better data and results visualizations (e.g. a strong interest in IU/UX)
• Draft data management plans
• Create sample IDs and laboratory test codes
• Securely transfer data to external project partners
• Enthusiastically explore regional and continental scale datasets
• Work with external front-end software developers to integrate existing Postgres databases into an online portal
• Publish work in addressing knowledge gaps in scientific peer review journals

We value diverse perspectives and recognize that each applicant for this role will bring unique skills, knowledge, and experience. Candidates who meet at least some of the criteria below are encouraged to apply. This position is appropriate for candidates with either an M.S. plus experience or a Ph.D. seeking a research-embedded, non-PI scientific role.

• Education:
  
  M.S. or Ph.D. in agronomy, soil science or other data science degree programs
• Experience:
  
  Demonstrated experience with accessing and updating relational databases; deep understanding of QA/QC processes; and communicating, sharing, and synthesizing data

• Strong proficiency in data processing using a modern data stack (Python, R, Postgre
  
  SQL) and cloud computing platforms
• Comfortable working in collaborative development environments (e.g., VS Code, Git)
• Experience integrating APIs and geospatial data
• Solid foundation in data analyses tools (visual synthesis, empirical modeling, empirical testing)
• Understanding and experience with agronomic, soil science, and natural resources data
• Aptitude for learning how to synthesize fresh data
• Ability to coordinate data collection from multiple laboratories and maintain positive working relationships with lab personnel
• Excellent interpersonal and communication skills
• Self-motivated and proactive, with the ability to thrive in a remote working environment
• Must be currently authorized to work for any employer in the United States and hold a valid U.S. driver’s license