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Machine Learning Geospatial Jobs in Florida (NOW HIRING)

... geospatial datasets and integrating AI/ML solutions into mission-critical applications. Education: * A Master's degree in Data Science, Machine Learning, Statistics, or a related field, or nine (9) ...

Experience with geospatial analytics or operational planning tools. * AWS Certified Machine Learning - Specialty, Microsoft Azure AI Engineer Associate, or similar cloud certification. * Security+ or ...

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Experience with geospatial analytics or operational planning tools. * AWS Certified Machine Learning - Specialty, Microsoft Azure AI Engineer Associate, or similar cloud certification. * Security+ or ...

Experience with geospatial analytics or operational planning tools. * AWS Certified Machine Learning - Specialty, Microsoft Azure AI Engineer Associate, or similar cloud certification. * Security+ or ...

New

Data Scientist

Tampa, FL · On-site

$120 - $190/hr

Experience with geospatial analytics or operational planning tools. * AWS Certified Machine Learning - Specialty, Microsoft Azure AI Engineer Associate, or similar cloud certification. * Security+ or ...

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Experience with geospatial analytics or operational planning tools.AWS Certified Machine Learning - Specialty, Microsoft Azure AI Engineer Associate, or similar cloud certification.Security+ or other ...

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Experience with geospatial analytics or operational planning tools. * AWS Certified Machine Learning - Specialty, Microsoft Azure AI Engineer Associate, or similar cloud certification. * Security+ or ...

New

Support or lead the development of machine-learning detectors and classifiers for sensor data ... sciences, geospatial analysis, information technology, resource management, conservation, and ...

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Showing results 41-60

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 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 cities in Florida are hiring for Machine Learning Geospatial jobs? Cities in Florida with the most Machine Learning Geospatial job openings:

Senior Data Scientist with Security Clearance

Prescient Edge

Doral, FL • On-site

Other

Medical, Dental, Vision, Retirement

Re-posted 7 days ago


Job description

Prescient Edge is seeking a Senior Data Scientist to support a federal government client. Please note that the availability of this position is contingent upon. Benefits: At Prescient Edge, we believe that acting with integrity and serving our employees is the key to everyone's success. To that end, we provide employees with a best-in-class benefits package that includes: * A competitive salary with performance bonus opportunities. * Comprehensive healthcare benefits, including medical, vision, dental, and orthodontia coverage. * A substantial retirement plan with no vesting schedule. Career development opportunities, including on-the-job training, tuition reimbursement, and networking. * A positive work environment where employees are respected, supported, and engaged. Description: * Design and implement advanced ML models and statistical methods to optimize forecasting, risk assessment, and decision-making processes. * Conduct data provenance tracking, ensuring documentation of sources, transformations, and lineage for compliance with governance policies. * Submit the Data Provenance & Lineage Report, summarizing transformation workflows, feature engineering processes, and audit compliance. Job Requirements Experience: * Possess the knowledge and capability to develop advanced machine learning models and optimize analytic workflows for predictive and prescriptive intelligence. * Personnel must be proficient in deep learning, supervised and unsupervised learning techniques, data wrangling, and feature engineering. * Experience with data provenance tracking, model explainability, and bias mitigation in AI/ML applications is required. * Personnel must be able to translate operational challenges into analytic solutions, ensuring integration of structured, unstructured, and geospatial data. * Personnel must have demonstrated experience in building and validating AI/ML models using Python, TensorFlow, PyTorch, or Scikit-learn, integrating models into production environments, and optimizing performance for real-time analytics. * Experience with Databricks, Apache Spark, or similar distributed data processing frameworks is required. * Personnel must also have experience working with geospatial datasets and integrating AI/ML solutions into mission-critical applications. Education: * A Master's degree in Data Science, Machine Learning, Statistics, or a related field, or nine (9) years of equivalent experience in AI/ML model development and deployment. * Desirable but not required certifications include Google Professional Machine Learning Engineer, Microsoft Certified: Azure Data Scientist Associate, or TensorFlow Developer Certification. Security clearance: * Active TS/SCI clearance. Location: * Doral, Florida. (USSOUTHCOM Headquarters) Prescient Edge is a Veteran-Owned Small Business (VOSB) founded as a counterintelligence (CI) and Human Intelligence (HUMINT) company in 2008. We are a global operations and solutions integrator delivering full-spectrum intelligence analysis support, training, security, and RD&E support solutions to the Department of Defense and throughout the intelligence community. Prescient Edge is an Equal Opportunity Employer (EEO). All applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic that is protected by law. We strive to foster equity and inclusion throughout our organization because we believe that diversity of thought is critical for creating a safe and engaging work environment while also enabling the organization's success.

Prescient Edge logo

About Prescient Edge

Sourced by ZipRecruiter

Prescient Edge is a prominent name in the global security industry, based out of McLean, VA, US. Established with the primary mission of harnessing science and technology for safety and security purposes, the company specializes in providing a wide range of products and services. This includes research and development, consulting, global operations support, intelligence evaluation, and advanced data solutions. These offerings make Prescient Edge an integral factor in national defense and commercial innovations.

Industry

Guided missile and space vehicle manufacturing

Company size

51 - 200 Employees

Headquarters location

McLean, VA, US

Year founded

2008

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