The Environmental Data Scientist at CUAHSI (https://cuahsi.org/) is responsible for leveraging advanced data science techniques and methodologies to support the broader water research community. The incumbent will serve as a data science expert, collaborating within a diverse research community to develop efficient and robust approaches for analyzing, accessing, and managing large and complex datasets from hydrology and various related disciplines. This position offers the opportunity to work remotely.

TO APPLY: Email your updated resume, with contact information, and any experience and qualifications relevant to this position include; share links to public code or wed products if available. Please include a cover letter that is less than a page in length. Send to: careers@cuahsi.org for consideration.

Key Responsibilities:

Data Analysis and Method Development:

• Utilize rigorous data science methods to analyze and help collaborative research teams extract insights from hydrologic and adjacent disciplinary (e.g., critical zone science) datasets.
• Develop innovative approaches to address complex data challenges with varied data formats, including high-resolution time-series observations, free-form text, imagery, and geospatial data.
• Create intuitive visualizations of spatiotemporal datasets to meet specific needs, such as QAQC, generating new hypotheses, and communicating water processes.
• Work directly with research community members to upskill their data handling techniques, utilizing programmatic approaches to data access, preparation, modeling, analysis, and dataset publication.

Data Workflow Implementation and Data Management:

• Design and implement methods for utilizing existing tools or data platforms (such as CUAHSI HydroShare, USGS NWIS) to facilitate data sharing and collaboration within the water research community.
• Create reference implementations of programmatic data access and data management techniques that can be customized for specific needs within the research community.
• Build highly usable data compilations that enable new synthesis questions to be addressed.
• Lead internal process improvement projects to automate the routine collection and presentation of various performance metrics (e.g., web usage, datasets published) and project budget analyses.

Community Engagement and Collaboration:

• Connect with research community members and technical staff to understand general data science needs and identify opportunities for new, broadly beneficial data science efforts.
• Collaborate with stakeholders to understand their requirements and develop customized data science solutions that address their specific needs.
• Encourage progress within the research community and lead by example with computational reproducibility, and CARE and FAIR data principles, presenting and/or designing/leading activities (such as hackathons) to meet these goals.

Team Collaboration and Vision Setting:

• Participate in interdisciplinary teams and project working groups within CUAHSI.
• Contribute to defining the vision for a future wider data science capability within CUAHSI, facilitating collaboration with academic, federal, and private sector data scientists.
• Actively engage with the community to understand their requirements and incorporate their feedback into the development of data science initiatives.