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Spatial Data Jobs in Michigan (NOW HIRING)

Varsity Tutors

High School Geography Tutor

Detroit, MI · Remote

$40/hr

Skilled at teaching map interpretation, spatial analysis, and geographic reasoning. Guides students through reading topographic and thematic maps, analyzing population data and migration patterns ...

University of Michigan

RESEARCH FELLOW

Ann Arbor, MI · On-site

... and spatial transcriptomics, ATAC-seq) and quantitative imaging (including confocal microscopy ... Analyze and interpret data using appropriate computational/statistical approaches; maintain ...

Trilon Group

In this role, you will provide spatial and graphical interpretation of environmental analytical data, including but not limited to contaminant maps, geophysical maps and potentiometric and other ...

Trilon Group

G.I.S.

Houghton, MI · On-site

Provide spatial and graphical interpretation of environmental analytical data, including but not limited to contaminant maps, geophysical maps, and potentiometric and other surface maps * Manage ...

Stem Xpert

Oracle Database Developer

Lansing, MI

They will be writing complex SQL statements including spatial queries using Oracle's SDO_Geometry data type. They will be using Data Definition Language (DDL) and Data Manipulation Language (DML) to ...

Cavnue

Senior Software Engineer - Core

Detroit, MI · Remote

$121.30K - $159.90K/yr

This is a broad, hands-on role working across the full depth of our platform, including building data replay infrastructure for system validation, aggregating traffic data over spatial and temporal ...

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All JobsSpatial Data JobsSpatial Data Jobs in Michigan

Spatial Data information

See Michigan salary details

$38.8K

$113.1K

$154.7K

How much do spatial data jobs pay per year?

As of May 29, 2026, the average yearly pay for spatial data in Michigan is $113,060.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,800.00 and $119,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Spatial Data Analyst, and why are they important?

To excel as a Spatial Data Analyst, you need a strong background in geography, GIS, data analysis, and a relevant degree such as geography, environmental science, or computer science. Proficiency in GIS software (e.g., ArcGIS, QGIS), spatial databases (like PostGIS), and programming languages such as Python or R is typically required. Strong problem-solving abilities, attention to detail, and effective communication skills distinguish top performers in this field. These competencies are essential for accurately interpreting spatial data, generating actionable insights, and effectively sharing findings with stakeholders.

What are some typical challenges faced by spatial data analysts when working with large geospatial datasets?

Spatial data analysts often encounter challenges related to data quality and integration when working with large geospatial datasets. Issues such as inconsistent data formats, missing metadata, and varying spatial resolutions can complicate analysis. Additionally, managing the computational load of processing and visualizing large, complex datasets may require specialized software and robust hardware. Collaborating closely with GIS specialists, IT teams, and data engineers helps to address these challenges and ensure reliable results.

What is spatial data?

Spatial data, also known as geospatial data, refers to information about the physical location and shape of objects on Earth. This data is usually stored as coordinates and topology and can represent features such as buildings, roads, rivers, or even entire countries. Spatial data is used in mapping, geographic information systems (GIS), urban planning, environmental studies, and various other fields to analyze locations, patterns, and relationships. It can be stored in formats like vector (points, lines, polygons) or raster (grids, images). Understanding spatial data is essential for making informed decisions based on geographic information.

What is the difference between Spatial Data vs GIS Analyst?

AspectSpatial DataGIS Analyst
Required CredentialsGIS certifications, degrees in geography, GIS, or related fieldsGIS certifications, degrees in geography, GIS, or related fields
Work EnvironmentData collection, database management, mapping softwareData analysis, map creation, spatial problem-solving
Employer & Industry UsageUsed by GIS professionals, urban planners, environmental agenciesEmployed in government, consulting firms, environmental organizations
Search & Comparison IntentUnderstanding data types, data managementAnalyzing spatial data, creating maps, reports

Spatial Data refers to the raw geographic information used in mapping and analysis, while a GIS Analyst actively interprets, analyzes, and visualizes this data to support decision-making. Both roles require similar credentials and are integral to GIS projects, but Spatial Data is the foundational information, whereas GIS Analysts focus on applying that data to solve spatial problems.

What are popular job titles related to Spatial Data jobs in Michigan? For Spatial Data jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Spatial Data jobs in Michigan look for? The top searched job categories for Spatial Data jobs in Michigan are:
Spatial Data jobs near you
Assistant Scientist / Assistant Professor - Computational Biology

Assistant Scientist / Assistant Professor - Computational Biology

Henry Ford Medical Group

Detroit, MI

Other

Posted 15 days ago

Job description

Henry Ford Health

Henry Ford Health (HFH) in Detroit, Michigan, is one of the nation's leading comprehensive health systems, recognized for excellence in clinical care, research, and education. The Center for Cutaneous Biology and Immunology (CCBI) is a dynamic, multidisciplinary research program dedicated to advancing our understanding of skin biology and immunology, cancer immunology, and the functional genomics that govern immune cell behavior in cancer as well as autoimmune and inflammatory diseases. Our team fosters an innovative, collaborative, diverse, and open-minded research environment in partnership with Michigan State University. We are supported by multiple NIH-funded grants and active communities of immunologists, molecular biologists, biochemists, data scientists, physician scientists, and computational biologists. Our mission is to advance translational research that leads to meaningful improvements in clinical care.

Position Description

We invite applications for an Assistant Professor / Assistant Scientist with expertise in computational biology, statistical genetics, genomics, and AI-driven medicine. We seek a highly motivated individual who develops and applies state-of-the-art computational methods to complex, large-scale biological datasets. The successful candidate will contribute to high-impact translational research programs and lead independent research efforts, and will hold a joint faculty appointment (Assistant Scientist) with Michigan State University as part of the HFH-MSU Health Sciences partnership.

Key Responsibilities

  • Develop and apply computational, statistical, and AI/ML approaches to analyze diverse biological datasets, including:
    • GWAS, whole-genome/exome sequencing
    • DNA methylation and epigenomic profiling
    • Bulk and single-cell RNA-seq, spatial transcriptomics
    • ATAC-seq (bulk and single-cell), proteomics, CyTOF, and IMC
    • Histological and radiological imaging data
    • Clinical and epidemiological datasets
  • Lead independent research projects and contribute to collaborative team science initiatives.
  • Pursue external funding (e.g., NIH, NSF, foundations) to support research programs.
  • Mentor trainees and collaborate closely with investigators across HFH and Michigan State University.

Required Qualifications

  • PhD in biostatistics, bioinformatics, computational biology, computer science, or a related discipline.

  • Strong research track record in genetics, multi-omics integration, and/or AI applications to biological or clinical data, as demonstrated by peer-reviewed publications and conference presentations.

  • Demonstrated ability-or strong potential-to secure external research funding.

  • Proficiency in programming and analytical languages/platforms (e.g., R, Python, TensorFlow, PyTorch).

  • Experience working in Unix/Linux environments, including shell scripting (Bash, awk, sed).

  • Familiarity with tools for genomic, epigenomic, transcriptomic, and proteomic analysis, including next-generation sequencing pipelines (DNA-seq, RNA-seq, ATAC-seq, ChIP-seq).

  • Experience with single-cell and spatial transcriptomics, eQTL/pQTL analysis, and multimodal data integration.

  • Familiarity with imaging analytics (e.g., spatial transcriptomics, H&E, IMC, radiological imaging).

  • Experience in human subjects research, healthcare data, epidemiology, or biomedical applications.

  • Excellent communication, interpersonal, organizational, and collaborative skills, with the ability to work effectively with colleagues of diverse technical and scientific backgrounds.

How to Apply:

Please submit your CV, cover letter, and research statement (past accomplishments, current work, and future research vision) to:

Dr. Qing-Sheng Mi, MD, PhD

Director, Center for Cutaneous Biology and Immunology (CCBI)

Email: qmi1@hfhs.org

Equal Employment Opportunity/Affirmative Action Employer

Henry Ford Health is committed to the fair and equitable treatment of all individuals and prohibits discrimination based on race, color, creed, religion, age, sex, national origin, disability, veteran status, marital or family status, gender identity, sexual orientation, height, weight, genetic information, or any other protected category in accordance with federal and state laws.

Additional Information
  • Organization: Henry Ford Medical Group
  • Department: Dermatology - New Center Det
  • Shift: Day Job
  • Union Code: Not Applicable

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