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Machine Learning Geospatial Jobs in South Carolina

Lynker Corporation

Geospatial Analyst

Charleston, SC · On-site +1

$55K - $72K/yr

Knowledge or experience related to land cover classification using machine learning or more ... sciences, geospatial analysis, information technology, resource management, conservation, and ...

Lynker Corporation

Geospatial Analyst

Charleston, SC · On-site +1

$55K - $72K/yr

Seeking a Geospatial Analyst to support the National Oceanic and Atmospheric Administration's (NOAA ... Knowledge or experience related to land cover classification using machine learning or more ...

Lynker Corporation

Geospatial Analyst

Charleston, SC · On-site +1

Knowledge or experience related to land cover classification using machine learning or more ... sciences, geospatial analysis, information technology, resource management, conservation, and ...

Motorola

Senior DevOps Engineer (US REMOTE)

Lexington, SC · Remote

$140K - $170K/yr

The solutions we create apply exciting technologies such as geospatial visualization and analytics ... Experience with AI/machine learning technologies is strongly preferred. * Familiarity with TCP/IP ...

All JobsMachine Learning Geospatial JobsMachine Learning Geospatial Jobs in South Carolina

Machine Learning Geospatial information

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

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 job categories do people searching Machine Learning Geospatial jobs in South Carolina look for? The top searched job categories for Machine Learning Geospatial jobs in South Carolina are:
What cities in South Carolina are hiring for Machine Learning Geospatial jobs? Cities in South Carolina with the most Machine Learning Geospatial job openings:
Machine Learning Geospatial jobs near you
Geospatial Analyst

Geospatial Analyst

Lynker Corporation

Charleston, SC • On-site, Remote

$55K - $72K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 29 days ago

Job description

Overview
Seeking a Geospatial Analyst to support the National Oceanic and Atmospheric Administration's (NOAA) Office for Coastal Management (OCM) by performing processing, quality assurance, documentation, and management of remote sensing and geospatial data and services. The ideal Geospatial Analyst will be located in the Charleston, SC area and will be able to work in a hybrid capacity.
The successful candidate will serve as a geospatial analyst in OCM's Science and Geospatial Services Division supporting NOAA's Coastal Change Analysis Program (C-CAP) activities. The position will be focused primarily on land cover data production, quality assurance reviews, and analyses but may also include work with imagery, Lidar data, and Digital Elevation Models. This role is contingent upon contract award.
Responsibilities
Core responsibilities of the Geospatial Analyst will include, but are not limited to:
  • Quality assurance of land cover datasets at multiple resolutions
  • Assisting with direct land cover data classification and development using multiple sources of input data
  • Compiling, processing, and analyzing a variety of data types, including imagery, elevation, and/or other geographic based ancillary data, in both raster and vector formats
  • Possible produce derived products, such as maps, statistics, and other information.
  • Works as part of a team and independently to achieve day-to-day objectives and operational results for project deliverables.
  • Responsible for major project components or processes, including managing complex, automated tasks; assisting with publishing and managing map services; writing metadata records; and the development of derivative products (ex. Storymaps, web apps, etc.)

Qualifications
The Geospatial Analyst should have the following:
  • Master's degree with two plus years of related experience in geography, remote sensing, GIS, or related field OR a Bachelor's degree with six plus years of related experience
  • Some experience or general knowledge of land cover mapping methods, elevation data, orthoimagery analysis, and change detection
  • Some experience or general knowledge with both raster and vector-based datasets on desktop and web-based platforms
  • Some experience or general knowledge of geospatial analysis tools such as (or similar to) ArcGIS Pro, Erdas Imagine, QGIS, Global Mapper, Trimble eCognition, FeatureAnalyst, etc.
  • Strong communication and organizational skills and excellent interpersonal skills
  • Self-starter with ability to work in a small team environment without direct day-to-day supervision
  • Ability to follow standard operating procedures and guidance documentation

The ideal Geospatial Analyst will have the following:
  • Knowledge or experience related to land cover classification using machine learning or more advanced deep learning artificial intelligence
  • Knowledge or experience with wetland mapping
  • Knowledge of Python scripting language required for automation of GIS tasks
  • Processing and managing data and map services in the cloud
  • Knowledge of coastal management and coastal processes
  • Knowledge of coastal hazards and inundation mapping

About Lynker
Lynker is a growing, employee owned, small business, specializing in professional, scientific and technical services. Our continually expanding team combines scientific expertise with mature, results-driven processes and tools to achieve technically sound, cost effective solutions in hydrology/water sciences, geospatial analysis, information technology, resource management, conservation, and management and business process improvement.
We focus on putting the right people in the right place to be effective. And having the right people is critical for success. Our streamlined organization enables and empowers our talented professionals to tackle our customers' scientific and technical priorities - creatively and effectively.
Lynker offers a team-oriented work environment, and the opportunity to work in a culture of exceptionally skilled professionals who embrace sound science and creative solutions. Lynker's benefits include the following:
  • Comprehensive healthcare for the employee at no monthly cost
  • Healthcare benefit covers medical, prescription drug, dental, and vision
  • Personal Time Off (PTO) Policy plus paid holidays
  • Highly competitive compensation plan regularly calibrated against industry and location benchmarks
  • 401(k) retirement plan with company-matching
  • Employee Stock Ownership Plan (ESOP) - we're all company owners!
  • Flexible spending accounts
  • Employee assistance program (EAP)
  • Short- and long-term disability insurance
  • Life and accident insurance
  • Tuition assistance/Training/Workforce improvement reimbursement per year
  • Spot bonuses for exceptional performance
  • Annual Employee Recognition Awards with bonuses
  • Employee Referral Program
  • Free centralized, self-directed Learning Management System to learn at your own pace
  • Personalized career growth plans for every employee

Lynker is an E-Verify employer.
Lynker is an equal opportunity employer and makes all employment decisions based on merit, qualifications, and business needs. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other legally protected status under federal, state, or local laws.
Fraud Alert: Recruitment Scam Warning: Lynker has been made aware of fraudulent individuals posing as Lynker recruiters and offering fake job opportunities. All legitimate Lynker job postings are listed on our official careers page. Communication from Lynker recruiters will come from an official @lynker.com email address.

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