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Gis Machine Learning Jobs in Massachusetts (NOW HIRING)

Lead Data Scientist

Northborough, MA ยท Hybrid

$153K - $180K/yr

Machine Learning expertise. * Python. * SQL. * Cloud Computing. * Database management experience. * Stakeholder communication skills. Preferred * Master's degree. * PhD. * GIS programming. * Energy ...

Lead Data Scientist

Waltham, MA ยท On-site

$153K - $180K/yr

Machine Learning expertise. * Python. * SQL. * Cloud Computing. * Database management experience. * Stakeholder communication skills. Preferred * Master's degree. * PhD. * GIS programming. * Energy ...

Lead Data Scientist

Waltham, MA ยท Hybrid

$153K - $180K/yr

Machine Learning expertise. * Python. * SQL. * Cloud Computing. * Database management experience. * Stakeholder communication skills. Preferred * Master's degree. * PhD. * GIS programming. * Energy ...

Data Scientist, Data Science

Waltham, MA ยท Hybrid

$103K - $121K/yr

In this role, you'll use advanced analytics, machine learning, and data science techniques to solve ... GIS programming knowledge or experience. * Experience in the energy industry or another regulated ...

Data Scientist, Data Science

Waltham, MA ยท On-site

$103K - $121K/yr

In this role, you'll use advanced analytics, machine learning, and data science techniques to solve ... GIS programming knowledge or experience. * Experience in the energy industry or another regulated ...

Data Scientist, Data Science

Northborough, MA ยท Hybrid

$103K - $121K/yr

In this role, you'll use advanced analytics, machine learning, and data science techniques to solve ... GIS programming knowledge or experience. * Experience in the energy industry or another regulated ...

The Company's market-leading solutions, enhanced by AI and machine learning capabilities, provide ... Background in GIS, cartography, or geospatial data visualization. Experience with modern GIS ...

The Company's market-leading solutions, enhanced by AI and machine learning capabilities, provide ... Background in GIS, cartography, or geospatial data visualization. Experience with modern GIS ...

Gis Machine Learning information

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 cities in Massachusetts are hiring for Gis Machine Learning jobs?

Cities in Massachusetts with the most Gis Machine Learning job openings:

Temporary Graduate Research Assistant

Worcester Polytechnic Institute

Worcester, MA โ€ข On-site

$21/hr

Part-time

Posted 7 days ago


Job description

JOB TITLE
Temporary Graduate Research Assistant
LOCATION
Worcester
DEPARTMENT NAME
Fire Protection Engineering - JM
DIVISION NAME
Worcester Polytechnic Institute - WPI
JOB DESCRIPTION SUMMARY
We are seeking a highly motivated graduate student to join our research team in the Fire Protection Engineering Department at WPI. The position is focused on developing a Probabilistic Framework for Fire Risk Assessment using fire spread models in FireBench. The role requires a strong background in probabilistic modeling, data analysis, Python programming, and machine learning.
JOB DESCRIPTION
Skills and Experience:
  • Probabilistic Modeling: Experience with Monte Carlo simulation, Bayesian networks, or uncertainty quantification methods.
  • Python Programming: Proficiency in Python for data processing, simulation pipelines, and automation (NumPy, pandas, SciPy, etc.).
  • Machine Learning: Familiarity with ML frameworks (scikit-learn, TensorFlow, or PyTorch) for wildfire risk modeling and pattern recognition.
  • Geospatial Data Analysis: Experience handling large geospatial datasets (e.g., NOAA weather data, LANDFIRE fuel maps, GIS tools).
  • Fire Spread Models: Familiarity with fire behavior modeling tools such as FireBench, FARSITE, or WRF-SFIRE is a plus.
  • Excellent problem-solving skills, attention to detail, and ability to work independently and collaboratively.

Required Skills:
  • Python, Machine Learning, Monte Carlo Simulation, GIS/Geospatial Tools
  • Learning Outcomes Ability to Learn Quickly
  • Accuracy, Accurate Listening, Analytical Thinking
  • Collaboration, Communication, Data Analysis, Probabilistic Reasoning
  • Open Minded, Time Management, Verbal Communication

Job Requirements:
  • A current Master's candidate in Computer Science, Data Science, Robotics, Mechanical Engineering, or a related field is required.

Compensation:
Hourly rate is $21.00 based on experience. To apply please submit a cover letter and resume/cv
FLSA STATUS
United States of America (Non-Exempt)
WPI is an Equal Opportunity Employer. All qualified candidates will receive consideration for employment without regard to race, color, age, religion, sex, sexual orientation, gender identity, national origin, veteran status, or disability. It seeks individuals from all backgrounds and experiences who will contribute to a culture of creativity, collaboration, inclusion, problem solving, innovation, high performance, and change making. It is committed to maintaining a campus environment free of harassment and discrimination.