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Internship Geospatial Data Scientist Jobs in Michigan

Introduction to GIS, Introduction to Remote Sensing, Geospatial Analytics, Geospatial Data Management, and Digital Cartography and Geovisualization. A PhD in Geospatial Science or a closely-related ...

... geospatial data, and support transportation and infrastructure projects throughout the region. Why Tetra Tech: At Tetra Tech, we are Leading with Science to solve the world's most complex challenges.

... geospatial data, and support transportation and infrastructure projects throughout the region. Why Tetra Tech: At Tetra Tech, we are Leading with Science to solve the world's most complex challenges.

SAP Solution Architect

Auburn Hills, MI · On-site

$77.75 - $104.75/hr

Required : • Minimum of 8 years of relevant experience • Bachelor of Science in Computer ... geospatial data • Experience with Salesforce Integrations Company : In today's dynamic and ...

SAP Solution Architect

Auburn Hills, MI · On-site

$77.75 - $104.75/hr

Required : • Minimum of 8 years of relevant experience • Bachelor of Science in Computer ... geospatial data • Experience with Salesforce Integrations Company : Alpha Consulting Corp. has ...

Join our team of over 600 data scientists, design thinkers, immersive digital consultants, project ... Stay updated with the latest advancements in geospatial, analytical, and remediation technology and ...

Join our team of over 600 data scientists, design thinkers, immersive digital consultants, project ... Stay updated with the latest advancements in geospatial, analytical, and remediation technology and ...

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Internship Geospatial Data Scientist information

What is an internship geospatial data scientist?

An Internship Geospatial Data Scientist is a student or recent graduate who assists in analyzing and interpreting geographic data using advanced computational and statistical methods. They work with spatial datasets, use GIS (Geographic Information Systems) software, and may help develop models to solve real-world problems involving locations and spatial relationships. This internship provides hands-on experience in data analysis, mapping, and programming, preparing individuals for a career in geospatial science or data analytics.

What types of projects can an internship geospatial data scientist expect to work on, and how do these contribute to the organization's goals?

As an Internship Geospatial Data Scientist, you can expect to work on projects involving spatial data analysis, map creation, and data visualization using tools like GIS software and Python or R. These projects often support decision-making in areas such as urban planning, environmental monitoring, or logistics optimization. Interns typically assist in cleaning and processing large spatial datasets, developing models, and presenting findings to team members. Your contributions help inform strategic initiatives and provide actionable insights, offering valuable experience and exposure to real-world geospatial challenges.

What are the key skills and qualifications needed to thrive as an internship geospatial data scientist, and why are they important?

To thrive as an Internship Geospatial Data Scientist, you need a solid understanding of GIS concepts, spatial analysis, and proficiency in programming languages like Python or R, often supported by coursework or a background in geography, computer science, or related fields. Familiarity with tools such as ArcGIS, QGIS, remote sensing platforms, and data visualization software is typically expected. Strong analytical thinking, attention to detail, and effective communication skills help you interpret spatial data and collaborate with interdisciplinary teams. These abilities are crucial for delivering actionable geospatial insights and supporting data-driven decision-making within organizations.

What is the difference between Internship Geospatial Data Scientist vs Geospatial Data Analyst?

AspectInternship Geospatial Data ScientistGeospatial Data Analyst
Required CredentialsEnrolled in or recent graduate of relevant degree (e.g., GIS, Data Science)Similar educational background, often with additional certifications in GIS or analytics
Work EnvironmentInternship setting, often in tech, government, or environmental firmsFull-time or part-time roles in various industries like urban planning, environmental agencies
Employer & Industry UsageUsed by organizations seeking entry-level talent for geospatial projectsCommon in industries requiring spatial data analysis for decision-making

The Internship Geospatial Data Scientist is an entry-level role focused on learning and supporting geospatial data projects, often within a structured internship program. In contrast, a Geospatial Data Analyst is a more established position involving ongoing data analysis, reporting, and decision support. Both roles require similar educational backgrounds, but the internship is temporary and geared toward gaining experience, while the analyst role is typically permanent and more autonomous.

What are the most commonly searched types of Geospatial Data Scientist jobs in Michigan? The most popular types of Geospatial Data Scientist jobs in Michigan are:
What cities in Michigan are hiring for Internship Geospatial Data Scientist jobs? Cities in Michigan with the most Internship Geospatial Data Scientist job openings:

Data Scientist - Machine Learning Practitioner

BlueConduit

Ann Arbor, MI • On-site, Remote

$140K - $150K/yr

Full-time

Medical, Dental, Vision, Retirement

Re-posted 18 days ago


Job description

Company overview

BlueConduit is an infrastructure analytics SaaS company and social enterprise helping communities make better, faster, and more equitable decisions about critical water infrastructure. Our founding team pioneered predictive modeling for lead service line replacement in Flint, Michigan, and BlueConduit now works with hundreds of cities and utilities across North America.

Our platform helps utilities, municipalities, government agencies, and consultants combine fragmented infrastructure records, field observations, geospatial data, and predictive models to identify risk, prioritize work, meet compliance requirements, and communicate clearly with the public. We are a remote-first team committed to using data science for social good and building tools that are trusted by the people making high-stakes infrastructure decisions.

The role

BlueConduit is hiring a Data Scientist to improve and expand the machine learning models at the core of our infrastructure analytics platform. In this role, you will work on models that help cities prioritize infrastructure investments, reduce risk, and improve drinking water outcomes. You will strengthen our existing modeling workflows, help launch new model products and asset classes, and communicate results clearly to both technical and nontechnical audiences.

This is a strong fit for someone who combines rigorous applied ML judgment with product-minded execution: you enjoy messy real-world data, care about model validation and uncertainty, can build repeatable workflows rather than one-off analyses, and like explaining technical work to people who need to act on it.

In this role you will be expected to be using the latest available AI tools to code productively. You will need to understand what you're building and coding, and understand agentic AI workflows that involve best practices, including unit tests, built-in code reviews, and extensive documentation in your commits for fellow data scientists and software engineers.

This role reports to the VP of Data Science.

What you'll do
  • Build, validate, and improve machine learning and statistical models used in BlueConduit's infrastructure analytics products
  • Help design, build, and launch new model products and model classes that broaden the assets and risks BlueConduit can predict
  • Improve data science workflows, model evaluation, reproducibility, and handoffs into software/product systems
  • Work with heterogeneous municipal, infrastructure, geospatial, and field-observation datasets to generate actionable risk predictions
  • Design validation approaches and communicate model uncertainty, limitations, and tradeoffs clearly to internal teams and customers
  • Use modern AI coding tools such as Claude Code, Codex, or similar systems to accelerate development while applying strong independent programming judgment
  • Use multiple AI agents to contribute to extremely robust workflows and code pipelines with built-in testing and reviews
  • Support customer-facing analysis and present findings in ways that are clear, accurate, and useful for nontechnical decision-makers
  • Contribute to R&D that scales the impact, reliability, and reach of BlueConduit's predictive methods

BlueConduit is a small, remote, and growing team, so this is an opportunity to shape both the role and the next generation of our data science products.

What we're looking for
  • Strong Python-based data science experience, including pandas, NumPy, scikit-learn, and production-quality analysis workflows
  • An undergraduate degree in a quantitative field (e.g., CS, math, stats, physics)
  • Experience building, validating, and improving machine learning or statistical models on messy real-world data
  • Experience building repeatable data science workflows in a product at a SaaS company or similarly operational environment
  • Ability to communicate modeling results, uncertainty, and tradeoffs clearly to technical and nontechnical stakeholders
  • Fluency using modern AI coding tools - including coordinating work of AI agents - to accelerate development, grounded in strong independent programming ability and judgment
  • Strong data visualization, verbal communication, and written communication skills
  • Comfort with Git-based development workflows
  • Attention to detail, curiosity, and commitment to building models that are understandable, usable, and trusted by the people making infrastructure decisions
  • Passion for socially impactful data science, environmental justice, and public-interest technology
We're especially interested in candidates with one or more of the following
  • A rigorous graduate degree in a quantitative field, or equivalent applied experience
  • Experience modeling asset classes beyond BlueConduit's current water distribution portfolio, such as fire risk, wastewater, hydraulic systems, climate risk, insurance risk, or other infrastructure domains
  • Experience with geospatial data, GIS systems, GeoPandas, or spatial modeling
  • Experience creating a new model product or extending an existing model product to a new domain or asset class
  • Experience with both global/cross-location models and local/site-specific models
  • Experience with methodologies beyond classical ML, such as neural networks, transformers, transfer learning, or other modern ML approaches
  • Experience with cloud-based model workflows, model tracking, versioning, Databricks, PySpark, or distributed computing
  • Familiarity with infrastructure, water quality, government data, or regulated public-sector decision environments
  • Experience working in Agile product development environments
  • Aptitude and interest in building with rapid iteration cycles involving prototyping, receiving feedback, and rebuilding
Location

Remote

Compensation
  • Expected salary range: $140,000-$150,000, commensurate with experience
  • Equity options
  • Health, vision and dental benefits
  • Simple IRA benefit with company contribution matching

Every qualified applicant will receive consideration for employment without regard to race, age, color, religion, sex, sexual orientation, or national origin.

Employment Type: FULL_TIME