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Gis Machine Learning Jobs in Georgia (NOW HIRING)

Design, build, and maintain machine learning and statistical models that support ongoing ... Leverage BI, GIS, and visualization tools to clearly communicate insights to technical and non ...

The role involves applying advanced statistical, computational, and machine learning techniques to ... Employ geospatial scientific principles and GIS tools to integrate location‑based data and models ...

The role involves applying advanced statistical, computational, and machine learning techniques to ... Employ geospatial scientific principles and GIS tools to integrate location-based data and models ...

The role involves applying advanced statistical, computational, and machine learning techniques to ... Employ geospatial scientific principles and GIS tools to integrate locationbased data and models ...

Expertise in modern Machine Learning (ML) methods (supervised/unsupervised learning, time series ... GIS mapping skills using Tableau, Surfer, or ArcGIS/ESRI * Background in Economics, Finance, and/or ...

Data Analyst, Senior

Atlanta, GA · On-site +1

$64K - $87K/yr

Experience with open-source GIS tools is a plus. oData Visualization: Ability to design clear ... Familiarity with machine learning methods is a plus. • Domain Knowledge: Working familiarity with ...

... machine learning systems and evolving to support broader data and intelligence use cases. In this ... Experience building or leading domain-specific data platforms (e.g., AEC, BIM, GIS, manufacturing ...

... learning. With nearly 100 years of experience, we're still discovering new ways to make lives ... Operating machinery, power tools, and motor vehicles are also required. Some travel (approximately ...

... learning.With nearly 100 years of experience, we're still discovering new ways to make lives better ... Operating machinery, power tools, and motor vehicles are also required. Some travel (approximately ...

... learning. With nearly 100 years of experience, we're still discovering new ways to make lives ... Operating machinery, power tools, and motor vehicles are also required. Some travel (approximately ...

Gis Machine Learning information

What are GIS Machine Learning jobs?

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 some common challenges faced 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 Georgia are hiring for Gis Machine Learning jobs? Cities in Georgia with the most Gis Machine Learning job openings:
Infographic showing various Gis Machine Learning job openings in Georgia as of May 2026, with employment types broken down into 99% Full Time, and 1% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution.
Data Scientist - Atlanta, GA

Data Scientist - Atlanta, GA

Cortland

Atlanta, GA

Other

Posted 26 days ago


Cortland rating

9.3

Company rating: 9.3 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

2nd of 153 rated real estate companies


Job description

Role Overview

As a Data Scientist, you'll design and deploy advanced analytics and machine learning solutions that address critical investment and operational challenges. Your work will transform complex data into scalable, productionready insights that drive smarter decisions and accelerate Cortland's growth.

  • Partner with business stakeholders to identify, prioritize, and deliver highvalue predictive and optimization use cases.
  • Design, build, and maintain machine learning and statistical models that support ongoing operational and investment strategies.
  • Collaborate with data and engineering teams to establish the infrastructure, pipelines, and processes required for production analytics.
  • Develop endtoend solutions, including model development, deployment, monitoring, and continuous improvement.
  • Leverage BI, GIS, and visualization tools to clearly communicate insights to technical and nontechnical audiences.
  • Lead enablement and education efforts to help teams effectively adopt and operationalize predictive analytics.
  • Stay current on emerging data science tools, platforms, and methodologies, bringing relevant innovations into the organization.

Qualifications 

  • Bachelor's degree in a STEMrelated field (e.g., statistics, applied math, computer science, engineering, business analytics) required; Advanced degree preferred.
  • 2+ years of professional experience applying data science or advanced analytics in a business environment
  • Strong foundation in statistical modeling, machine learning, clustering, classification, recommendation systems, and optimization techniques
  • Proficiency in Python and SQL; experience with Spark, Scala, or similar tools is a plus
  • Working knowledge of cloud platforms and data ecosystems (AWS or Azure), including tools such as Databricks, EMR, RDS, and S3
  • Experience working with large, complex datasets and resolving performance or memory constraints
  • Solid business intuition with the ability to explain analytical approaches, tradeoffs, and outcomes clearly
  • Excellent communication skills, with the ability to present insights visually and tell a compelling datadriven story