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Gis Machine Learning Jobs in Newton, MA (NOW HIRING)

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Gis Machine Learning information

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$15

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$53

How much do gis machine learning jobs pay per hour?

As of Sep 8, 2026, the average hourly pay for gis machine learning in Newton, MA is $31.29, according to ZipRecruiter salary data. Most workers in this role earn between $23.75 and $36.92 per hour, depending on experience, location, and employer.

What is a GIS Machine Learning job?

GIS Machine Learning jobs involve applying machine learning techniques to geographic information systems (GIS) data to analyze spatial patterns, make predictions, and solve complex geospatial problems. Professionals in this field use algorithms and models to process location-based data, automate mapping tasks, and extract insights from satellite imagery or sensor data. These roles often require skills in programming, data analysis, and an understanding of both GIS principles and machine learning methodologies. GIS Machine Learning specialists can work in industries like urban planning, environmental monitoring, agriculture, and disaster management.

What are common challenges when integrating machine learning models with GIS data, and how can they be addressed?

One common challenge in GIS machine learning roles is handling the complexity and diversity of spatial data, which often comes in various formats and resolutions. Ensuring data quality and alignment is crucial, as inconsistencies can negatively impact model performance. Another challenge is computational efficiency, since spatial datasets can be very large. Collaboration with data engineers and GIS analysts is often necessary to preprocess data effectively and optimize workflows. Staying updated with advancements in geospatial libraries and cloud-based solutions can help address these challenges.

What are the key skills and qualifications needed to thrive as a GIS Machine Learning specialist, and why are they important?

To thrive as a GIS Machine Learning Specialist, you need expertise in geospatial analysis, machine learning algorithms, and a background in GIS-related fields, often supported by a relevant degree. Familiarity with tools like ArcGIS, QGIS, Python, R, and libraries such as scikit-learn and TensorFlow, as well as experience with spatial databases, is crucial. Strong problem-solving, critical thinking, and effective communication skills help translate complex data into actionable insights. These abilities enable professionals to develop innovative geospatial solutions and drive informed decision-making in diverse sectors.

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

AspectGis Machine LearningGIS Analyst
Required CredentialsBachelor's in GIS, Computer Science, or related; knowledge of machine learningBachelor's in Geography, GIS, or related; GIS certifications often preferred
Work EnvironmentData science teams, software development, research projectsUrban planning, environmental agencies, government offices
Employer & Industry UsageTech companies, research institutions, environmental firmsGovernment agencies, consulting firms, urban planning departments
Common Search & Comparison IntentUnderstanding technical skills and data modelingAnalyzing spatial data for projects and reports

Gis Machine Learning focuses on applying machine learning techniques to spatial data, often requiring programming and data science skills. In contrast, GIS Analysts primarily work with spatial data analysis, mapping, and reporting within various industries. While both roles involve GIS, Gis Machine Learning emphasizes advanced data modeling, whereas GIS Analysts focus on spatial data management and visualization.

What are popular job titles related to Gis Machine Learning jobs in Newton, MA?

For Gis Machine Learning jobs in Newton, MA, the most frequently searched job titles are:

What job categories do people searching Gis Machine Learning jobs in Newton, MA look for?

The top searched job categories for Gis Machine Learning jobs in Newton, MA are:

Gis Machine Learning jobs near you

HMS - Research Associate in Biomedical Informatics (Patel Lab)

Harvard University

Cambridge, MA • On-site

$90K - $120K/yr

Full-time

Re-posted 22 days ago

Harvard University rating

8.5

Company rating: 8.5 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

82nd of 631 rated colleges and universities

Job description

Position
Details
Title
HMS - Research Associate in Biomedical Informatics (Patel Lab)
School
Harvard Medical School
Department/Area
Biomedical Informatics
Position Description
Chirag Patel's group in the Department of Biomedical Informatics, Harvard Medical School, is seeking a Research Associate with a focus in Biomedical Informatics for geneby-exposome interactions and therapeutic discovery. Seeking an individual with a PhD to conduct research in the
area of biomedical informatics, multi-omic integratoin analytics and machine learning. In this role you will produce highly impactful biomedical informatics research that presents new innovations in methods and novel findings that inform disease etiology. The exposome is a promising and emerging modality to explain disease variation (papers in press in Nature Medicine) that impacts humans on all levels: from the single cell to populations, providing a rich substrate to do novel work. Candidates with experience in developing approaches to research and analyze large multi-modal datasets and who wish to deploy the next generation of exposome AI models are highly encouraged to apply. This position comes with data ready to analyze, and you can focus on developing research findings and writing papers from day 1.
Responsibilities include:
  • Research and translate exposome data science into real-world clinical applications.
  • Independently research and design exposome foundation models for disease physiology.
  • Characterize how an individual's exposome drives variation in response to pharmaceutical intervention.
  • Collaborate with interdisciplinary teams across Harvard (HSPH, HMS) and at partner universities to enhance data collection, cleaning, and integration processes, ensuring data accuracy and consistency.
  • Produce engineering outputs, including databases, application programming interfaces, apps.
  • Produce high-impact peer-reviewed articles, and presentations for academic and non-academic audiences.

Basic Qualifications
PhD in Data Science, Statistics, Computer Science,
Epidemiology, Environmental Health, or related field.
Additional Qualifications
  • Demonstrated expertise in large scale analysis and familiarity with health-related datasets.
  • Proficiency in statistical software (R, Python, etc.), and working knowledge of data management protocols.
  • Experience with exposome or environmental data, multiomics integration, and exposure-wide association studies (ExWAS) and GIS preferred

Special Instructions
Required documents:
  • Curriculum Vitae
  • Statement of Research for PhD work
  • Cover Letter describing your interest in the lab and initial ideas for new research directions or projects you could undertake in the lab.
  • Note with names and contact information for three people who have agreed to serve as your reference

Please submit application documents through the ARIeS portal.Selected candidates will be invited for in-person interviews involving a research presentation on past work.
Expected Dates
  • Duration: This is a one-year term position from the date of hire, with the possibility of extension, contingent upon work performance, business need, and continued funding to support the position.

Contact Information
Nichole Parker
10 Shattuck St
Boston, MA 02115
Contact Email
nichole_parker@hms.harvard.edu
Salary Range
$90K-$120K
Minimum Number of References Required
3
Maximum Number of References Allowed
3
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