Über
Job code: 9791IF
Employee Group: P&A Full/Part Time: 1 FTE; 100% Regular/Temporary: Regular
U-Spatial is seeking a Geospatial Data Scientist / Research Data Analyst to design and implement a sustainable, graph-based data infrastructure integrating diverse research and administrative datasets from across the University of Minnesota. The 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—to re-mapping rather than restructuring the University. Through knowledge-link and geographic visualization, we 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, and the Research Development Office, this role will help create interactive maps, dashboards, and visualization tools that clarify internal expertise and connect the University to public, private, and non-profit partners across the state and beyond.
Location: Duluth (Kirby Plaza) or Twin Cities (Blegen Hall). Hybrid work available with profiles 1-3 as described (fully on-site, on-site 3+ days per week, primarily remote).
Primary Responsibilities
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., 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.
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.
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.
Qualifications 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.
Pay and Benefits Pay Range:
$87,000 - $105,000 (depending on education/qualifications/experience)
Competitive wages, paid holidays, and generous time off
Continuous learning opportunities through professional training and degree-seeking programs supported by the Regents Tuition Benefit Program
Low-cost medical, dental, and pharmacy plans
Healthcare and dependent care flexible spending accounts
University HSA contributions
Disability and employer-paid life insurance
Employee wellbeing program
Excellent retirement plans with employer contribution
Public Service Loan Forgiveness (PSLF) opportunity
Financial counseling services
Employee Assistance Program with eight sessions of counseling at no cost
Employee transit pass with free or reduced rates in the Twin Cities metro area
Diversity and Inclusion 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: http://diversity.umn.edu
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Sprachkenntnisse
- English
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