Job Description

Required Qualifications:

• Advanced degree in data science, geography, GIS, informatics, or a related field, with at least one year of research training or equivalent experience.
• Demonstrated experience with graph databases (e.g., Neo4j, ArangoDB), Cypher query language, and familiarity with RDF or semantic web concepts.
• Strong proficiency in Python and SQL, including practical experience delivering production-level ETL/ELT workflows.
• Experience with data cleaning, quality assurance, and reproducible analytical processes.
• Demonstrated ability to translate domain researchers’ scientific questions into scalable data models and analytical strategies.
• Experience designing and implementing data pipelines for geospatial datasets, including spatial attributes and place-based linkage.
• Experience working with large, complex datasets that may require novel data structures, indexing strategies, or parallelized workflows.
• Ability to work independently with periodic guidance in a collaborative research environment.

Preferred Qualifications:

• Experience with ArcGIS Knowledge or comparable graph-enabled GIS environments.
• AI bot development (Botpress, Microsoft's Copilot Studio, etc).
• PhD in data science, geography, GIS, informatics, or a related field.
• Experience in GIS, geospatial computing, or satellite/drone imagery processing.
• Experience developing semantic layers, ontologies, or structured knowledge models.
• Experience with program evaluation, impact assessment, or data-driven decision support.

Title: Geospatial Data Scientist / Research Data Analyst
Job code: 9791IF
Employee Group: P&A
Full/Part Time (FTE): 1 FTE; 100%
Regular/Temporary: Regular


About the Job:
U-Spatial is seeking a Geospatial Data Engineer / Research Data Analyst to design and implement a sustainable, graph-based data infrastructure that integrates diverse research and administrative datasets from across the University of Minnesota. This role centers on developing a curated graph database environment (e.g., ArcGIS Knowledge, Neo4j) that represents entities such as people, projects, grants, publications, places, and outputs—and models their relationships over time. The position will build robust Python-based ETL/ELT pipelines, implement SQL transformations, harmonize identifiers, manage slowly changing attributes, and create repeatable ingestion workflows with testing, logging, and validation. A documented source-to-graph mapping for priority datasets and a researcher-friendly data dictionary will ensure that the infrastructure is transparent, reproducible, and scalable.


Beyond technical development, this position advances a broader strategic goal - re-mapping rather than restructuring the University. Through knowledge-link and geographic visualization, we will identify intersections across disciplines, strengthen social and intellectual capital, and increase competitiveness for large interdisciplinary proposals. Working in partnership with the Learn–Innovate–Network–Collaborate (LINC) initiative, the Office of Public Engagement, the Research Development Office, this role will help create interactive maps, dashboards, and visualization tools that clarify internal expertise and connect the University to various public, private, and non-profit partners across the state and beyond.


Location and Work environment:
This position is based on either the Duluth (Kirby Plaza) or Twin Cities (Blegen Hall) campus. This position allows for a hybrid work option - full-time remote work is not an option. This position is eligible for work profile 1 (fully on-site), work profile 2 (on-site at least 3 days per week), or work profile 3 (primarily remote, working on-site 1-2 days per week).


Work Schedule:
N/A (not labor represented)


Primary Responsibilities:
Development of Analytic Models and Tools (70%)

• Design, develop, and maintain Python-based ETL/ELT workflows that ingest research and administrative datasets from multiple sources.
• Lead data transformation and modeling efforts, including harmonizing identifiers, defining entities and relationships, and managing slowly changing attributes.
• Implement SQL-based transformations and curated extracts to support reporting, analytics, and downstream applications.
• Build, load, and maintain one or more labelled property graph databases (e.g. using ArcGIS Knowledge, Neo4j or equivalent), including schema design, constraints, indexing strategies, and repeatable, validated load processes.
• Produce well-documented, reproducible data products and extracts to support research teams and strategic initiatives.
• Design and implement informatics strategies that integrate geospatial attributes, place-based linkage, and remote sensing data as appropriate.
• Demonstrated experience using generative AI tools (e.g., large language models) effectively, including prompt design, evaluation of outputs, and responsible use in professional or research settings.
• Collaborate effectively with researchers and staff across a wide range of technical backgrounds.

Education and Consulting (20%)

• Partner with faculty, librarians, and data stewards to develop controlled vocabularies, ontologies, and documentation standards.
• Develop and deliver training materials, workshops, and technical guidance to support adoption and responsible use of the data infrastructure.
• Serve as Principal Investigator (PI) or project lead on selected initiatives, managing scope, timelines, and deliverables as needed.

Professional Development (10%)

• Experience developing, fine-tuning, or integrating large language models (LLMs) into applications or research workflows.
• Engage in relevant professional forums, conferences, and scholarly communities to ensure alignment with emerging best practices.

With offices on both the Twin Cities and Duluth campuses, U-Spatial collaborates with a variety of departments and centers, creating new opportunities and synergies around spatial research, teaching, and service by supporting projects with application development and spatial analysis.


U-Spatial is a nationally recognized model that advances the fast-growing need for expertise in Geographic Information Systems (GIS), remote sensing, and spatial computing. The infrastructure eliminates duplication and fragmentation of resources by providing a framework of spatial data, equipment, and expertise. U-Spatial has supported over 3,000 researchers across every department and center at the University through the help desk, training, consulting, and events. U-Spatial has been integral to making the U of M one of the world’s first "Spatial Universities".


Organizationally, U-Spatial is within Research Computing, an academic center within Research and Innovation Office (RIO). Research Computing brings together the diverse portfolio of research computing and data resources available at the University. Research Computing currently houses five collaborative units that provide research computing expertise, resources, training, and services across the University and beyond. These resources cover a broad range of research needs, from consultation and collaboration with domain experts, to hardware and software resources, to education and training in computational methods and technologies.

Applications must be submitted online. To be considered for this position, please click the Apply button and follow the instructions. You will be given the opportunity to complete an online application for the position and attach a cover letter and resume.

Additional documents may be attached after application by accessing your "My Job Applications" page and uploading documents in the "My Cover Letters and Attachments" section.

To request an accommodation during the application process, please e-mail employ@umn.edu or call (612) 624-8647.

The University recognizes and values the importance of diversity and inclusion in enriching the employment experience of its employees and in supporting the academic mission. The University is committed to attracting and retaining employees with varying identities and backgrounds.

The University of Minnesota provides equal access to and opportunity in its programs, facilities, and employment without regard to race, color, creed, religion, national origin, gender, age, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U:

Any offer of employment is contingent upon the successful completion of a background check. Our presumption is that prospective employees are eligible to work here. Criminal convictions do not automatically disqualify finalists from employment. Visa sponsorship, including H-1B, may be considered for qualified candidates whose visa circumstances do not require payment of the $100,000 H-1B fee.

The University of Minnesota, Twin Cities (UMTC)

The University of Minnesota, Twin Cities (UMTC), is among the largest public research universities in the country, offering undergraduate, graduate, and professional students a multitude of opportunities for study and research. Located at the heart of one of the nation's most vibrant, diverse metropolitan communities, students on the campuses in Minneapolis and St. Paul benefit from extensive partnerships with world-renowned health centers, international corporations, government agencies, and arts, nonprofit, and public service organizations.

At the University of Minnesota, we are proud to be recognized by the Star Tribune as a Top Workplace for 2021, as well as by Forbes as Best Employers for Women and one of America’s Best Employers (2015, 2018, 2019, 2023), Best Employer for Diversity (2019, 2020), Best Employer for New Grads (2018, 2019), and Best Employer by State (2019, 2022).

Job Tags

Full time, Temporary work, H1b, Work at office, Remote work, Visa sponsorship, Work visa, 2 days per week, 3 days per week, 1 day per week

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