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Machine Learning Geospatial Jobs in Minneapolis, MN

Experience with deep learning methods is desirable, but not required * Experience with geospatial ... Any unsolicited resume sent to Kitware, including to Kitware's mailing addresses, fax machines or ...

Experience with deep learning methods is desirable, but not required * Experience with geospatial ... Any unsolicited resume sent to Kitware, including to Kitware's mailing addresses, fax machines or ...

Experience with deep learning methods is desirable, but not required * Experience with geospatial ... Any unsolicited resume sent to Kitware, including to Kitware's mailing addresses, fax machines or ...

Machine Learning Geospatial information

See Minneapolis, MN salary details

$19

$30

$48

How much do machine learning geospatial jobs pay per hour?

As of Aug 22, 2026, the average hourly pay for machine learning geospatial in Minneapolis, MN is $30.42, according to ZipRecruiter salary data. Most workers in this role earn between $23.61 and $35.38 per hour, depending on experience, location, and employer.

What does a Machine Learning Geospatial professional do?

A Machine Learning Geospatial professional uses machine learning techniques to analyze and interpret geospatial data, such as satellite imagery, maps, and GPS data. Their work involves building and training models to detect patterns, make predictions, and solve spatial problems in fields like agriculture, urban planning, disaster response, and environmental monitoring. These professionals often collaborate with data scientists and GIS (Geographic Information Systems) specialists to extract actionable insights from large and complex geospatial datasets. Their skills are crucial for automating tasks such as image classification, land cover mapping, and object detection in geographic contexts.

What are the key skills and qualifications needed to thrive as a Machine Learning Geospatial professional?

To thrive as a Machine Learning Geospatial specialist, you need a strong background in machine learning, geospatial analysis, programming (Python, R), and a relevant degree in computer science, geography, or a related field. Familiarity with GIS software (e.g., ArcGIS, QGIS), remote sensing tools, and cloud platforms like Google Earth Engine or AWS is typically required. Analytical thinking, problem-solving, and effective communication are vital soft skills for interpreting data and collaborating with multidisciplinary teams. These skills and qualities are crucial for developing accurate geospatial models and delivering actionable insights from complex spatial data.

What are some common challenges faced by Machine Learning Geospatial professionals when integrating spatial data into predictive models?

Machine Learning Geospatial professionals often encounter challenges such as managing large and complex spatial datasets, ensuring data quality and consistency, and handling spatial autocorrelation that can bias model results. Additionally, integrating diverse data sources—like satellite imagery, sensor data, and GIS layers—requires advanced pre-processing and domain knowledge. Collaborating with GIS analysts and domain experts is usually essential to develop robust models that provide actionable insights.

What is the difference between Machine Learning Geospatial vs GIS Analyst?

AspectMachine Learning GeospatialGIS Analyst
Required CredentialsBachelor's or higher in Computer Science, Data Science, or related fields; knowledge of machine learning and geospatial dataBachelor's in Geography, GIS, or related fields; proficiency in GIS software
Work EnvironmentTech companies, data science teams, research institutionsGovernment agencies, urban planning, environmental firms
Industry UsageData-driven geospatial analysis, predictive modeling, AI applicationsMapping, spatial data management, spatial analysis

Machine Learning Geospatial professionals focus on applying machine learning techniques to analyze geospatial data, often working with large datasets and developing predictive models. GIS Analysts primarily handle spatial data management, mapping, and analysis using GIS software. While both roles work with geospatial data, Machine Learning Geospatial roles emphasize data science and AI, whereas GIS Analysts focus on spatial information management and visualization.

What are popular job titles related to Machine Learning Geospatial jobs in Minneapolis, MN?

For Machine Learning Geospatial jobs in Minneapolis, MN, the most frequently searched job titles are:

What job categories do people searching Machine Learning Geospatial jobs in Minneapolis, MN look for?

The top searched job categories for Machine Learning Geospatial jobs in Minneapolis, MN are:

Infographic showing various Machine Learning Geospatial job openings in Minneapolis, MN as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 23% Part Time, 1% Temporary, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $63,282 per year, or $30.4 per hour.

Utility Data and Modeling Analyst

HDR

Saint Louis Park, MN • On-site

Full-time

Re-posted 28 days ago


HDR rating

9.2

Company rating: 9.2 out of 10

Based on 59 frontline employees who took The Breakroom Quiz

33rd of 449 rated engineering


Job description

At HDR, our employee-owners are fully engaged in creating a welcoming environment where each of us is valued and respected, a place where everyone is empowered to bring their authentic selves and novel ideas to work every day. As we foster a culture of inclusion throughout our company and within our communities, we constantly ask ourselves: What is our impact on the world?
Watch Our Story:' https://www.hdrinc.com/our-story'
Each and every role throughout our organization makes a difference in our ability to change the world for the better. Read further to learn how you could help make great things possible not only in your community, but around the world.
We believe water is more than a resource, it's a shared responsibility. As part of our Water Business Group, you'll help shape how communities manage water for generations to come. From delivering safe drinking water and treating wastewater responsibly to developing sustainable water supplies and protecting lives and property through flood control, your work will directly support public health, environmental sustainability, and infrastructure resilience. We bring together experts across disciplines to solve complex challenges with bold thinking and technical excellence. Whether you're modernizing aging systems or pioneering innovative approaches, your contributions will make a meaningful difference in people's lives. This isn't just a job, it's a chance to lead change, drive progress, and leave a lasting legacy.
About the Role
HDR is seeking an entry-level Utility Data, Asset Management & Hydraulic Modeling Analyst to support water and wastewater utility projects through applied hydraulic modeling analysis, data analytics, GIS, and asset management. This position contributes to system evaluations, capital planning, regulatory analysis, and development of technical deliverables for municipal utility clients. The successful candidate will demonstrate strong analytical capability, technical rigor, and an interest in advancing data-driven utility planning.
Key Responsibilities:
Hydraulic Modeling & System Analysis
  • Assist with building and maintaining hydraulic model data for water distribution and wastewater collection systems using GIS datasets, as-built drawings, and field data.
  • Support hydraulic simulations, system performance evaluations, and scenario analyses for planning studies and operational assessments.
  • Utilize data from industry modeling tools such as InfoWater, InfoSewer, InfoSWMM, InfoWorks ICM, SewerGEMs, WaterGEMs, EPANet, and ArcGIS Pro.

Data Engineering, Analytics & Visualization
  • Perform data acquisition, cleaning, validation, and exploratory analysis on large datasets including SCADA data, metering data, GIS layers, and monitoring records.
  • Develop analytical and visualization outputs using SQL, Power BI, Python, R, and GIS platforms to support technical evaluations.
  • Support database management, data structuring, and creation of modeling-ready datasets to improve study reliability and documentation.
  • Handle highly sensitive and confidential information with professionalism and discretion
  • Collaborate with stakeholders to improve business decisions by identifying patterns and trends in data
  • Develop data products including reports, visualizations, and dashboards
  • Adhere to software and data science development standards
  • Perform data acquisition, sourcing, cleaning and exploratory data analysis (EDA)
  • Transform raw data into usable attributes for machine learning modules through feature engineering
  • Manage model lifecycle including development, deployment, data drift detection, model retraining, and model inference.
  • Create automated data pipelines and data engineering solutions
  • Develop advanced and custom predictive models (classification, regression, time series, neural networks, natural language processing, and computer vision)
  • Tune models with training, hyperparameters with comprehensive validation and testing processes

Asset Management & Capital Planning
  • Contribute to asset inventory development, condition assessment processes, and risk prioritization activities supporting water and wastewater capital planning.
  • Assist in preparing asset management and capital improvement plan documents, including risk modeling graphics, lifecycle analysis summaries, and decision-support exhibits.
  • Integrate asset, condition, and geospatial data to support long-term strategic planning for utility infrastructure.

Utility Planning, Policy Analysis & Technical Reporting
  • Support development of technical reports, planning documents, regulatory analyses, and client presentations.
  • Assist with evaluating impacts of evolving state and federal environmental policies on client utility systems.
  • Leverage predictive models to optimize business results
  • Contribute to studies involving financial planning, rate evaluation, and long-range system needs assessment.

Professional Collaboration
  • Actively participate in HDR's employee-owned, collaborative culture by working closely with multidisciplinary teams including engineers, planners, analysts, and project managers.
  • Communicate findings through written reports, visualizations, engineering graphics, and presentations.
  • Maintain high standards of quality control, documentation, and analytical accuracy.

Preferred Qualifications
  • Bachelor's Degree
  • A minimum of 3 years experience in a data science role
  • Foundational knowledge or academic experience in hydraulics, environmental systems, data analytics, GIS, or related disciplines.
  • Familiarity with or academic exposure to hydraulic modeling concepts or tools.
  • Experience with ArcGIS Desktop, ArcGIS Pro, or ArcGIS Online.
  • Oracle Spatial or SQL Server Spatial back-end data processing experience
  • Understanding of asset management principles such as condition assessment, risk scoring, or lifecycle planning.
  • Interest in environmental regulations and policy frameworks related to water and wastewater utilities.

#LI-EV1
Qualifications
Required Qualifications
  • A degree in a closely related field or combination of education and relevant experience
  • Self-motivated, detail-oriented professional, ability to multitask a must
  • Proficiency with MS Office including Word and Outlook
  • Proficiency with data engineering tools and languages such as SQL, Power Query, and Pandas
  • Proficiency with business intelligence tools such as Power BI, Tableau, Plotly, Seaborn, and Matplotlib
  • Proficiency with data science languages such as Python and R
  • Ability to handle confidential information
  • Excellent writing and people skills
  • Strong math and organizational skills
  • Flexibility and ability to prioritize and handle multiple tasks and various managers in a fast-paced environment
  • Excellent verbal and written communication skills including grammar, punctuation, proofreading, spelling and telephone skills
  • An attitude and commitment to being an active participant of our employee-owned culture is a must

What We Believe
HDR is our company. Together, we build on each other's life experiences and perspectives to make great things possible every day. This shapes our collaborative culture, encourages organizational trust and connects us closer to the clients and communities we serve.
Our Commitment
As employee owners, we all have a role in creating an inclusive environment where each of us is welcomed, valued, respected and empowered to bring our authentic selves to work every day.
Our eight Employee Network Groups (Asian Pacific, Black, Hispanic/Latino(a), LGBTQ+, People with Disabilities, Veterans, Women, Young Professionals) help create a sense of belonging and foster a supportive environment where everyone is empowered to engage and contribute. Each group has an executive sponsor and is open to all employees.

What HDR employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


HDR logo

About HDR

Sourced by ZipRecruiter

At HDR, we specialize in engineering, architecture, environmental and construction services. While we are most well-known for adding beauty and structure to communities through high-performance buildings and smart infrastructure, we provide much more than that. We create an unshakable foundation for progress because our multidisciplinary teams also include scientists, economists, builders, analysts and artists.

Industry

Specialized design services

Company size

5,001 - 10,000 Employees

Headquarters location

Omaha, NE, US

Year founded

1917