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Geospatial Data Scientist Jobs in Florida (NOW HIRING)

kgs

Data Scientist

Cape Canaveral, FL

Process and analyze large-scale geospatial datasets * Create data visualization and reporting ... Master's degree in Data Science, Computer Science, Statistics, Mathematics, or related field * 5+ ...

kgs

Data Scientist

Cape Canaveral, FL · On-site

Process and analyze large-scale geospatial datasets * Create data visualization and reporting ... Master's degree in Data Science, Computer Science, Statistics, Mathematics, or related field * 5+ ...

Prescient Edge

Senior Data Scientist

Doral, FL · On-site

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 ...

SOSi

Mid-Level Geospatial Research Analyst

Doral, FL · On-site

Support geospatial data collection, curation, and analysis, ensuring research outputs align with ... Bachelor's degree in Geography, Geospatial Science, GIS, Remote Sensing, Environmental Science ...

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Geospatial Data Scientist information

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$28K

$91.7K

$146.8K

How much do geospatial data scientist jobs pay per year?

As of Aug 23, 2026, the average yearly pay for geospatial data scientist in Florida is $91,721.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,600.00 and $101,600.00 per year, depending on experience, location, and employer.

What is a geospatial data scientist?

A Geospatial Data Scientist analyzes spatial and geographic data to extract insights, create predictive models, and support decision-making. They use tools like GIS, remote sensing, machine learning, and statistical analysis to process location-based data. Their work spans various industries, including urban planning, environmental monitoring, agriculture, and logistics. By leveraging spatial data, they help optimize operations, manage resources, and solve complex geographic problems.

What does a geospatial data scientist do?

As a Geospatial Data Scientist, your daily tasks often involve collecting, cleaning, and analyzing spatial datasets using GIS tools and programming languages. You may be responsible for developing spatial models, visualizing geographic data through interactive maps, and generating reports to help guide strategic decisions. Collaboration with professionals from engineering, urban planning, or environmental science teams is common, requiring you to communicate complex analyses in a clear and actionable manner. Additionally, you might participate in project meetings to align your work with organizational goals and stakeholder needs. This dynamic role blends technical analysis with communication and teamwork, making each day varied and intellectually stimulating.

What are the key skills and qualifications needed to thrive as a geospatial data scientist?

Geospatial Data Scientists require expertise in spatial analysis, statistics, and data modeling, typically supported by a degree in geography, computer science, or a related field. Proficiency with GIS software (such as ArcGIS or QGIS), programming languages like Python or R, and familiarity with spatial databases are often expected, while certifications in GIS can be advantageous. Strong problem-solving abilities, collaboration, and effective communication skills help professionals translate complex data into actionable insights and work well with diverse teams. Mastery of these skills ensures accurate geospatial analyses and supports informed, data-driven decision making in various industries.

How much does a geospatial data scientist make?

A geospatial data scientist's salary typically ranges from $70,000 to $130,000 annually, depending on experience, education, location, and industry. Senior roles or those with specialized skills in GIS tools and programming may earn higher compensation.

Is geospatial data scientist still in demand?

Yes, geospatial data scientists are in high demand due to the increasing use of geographic information systems (GIS), remote sensing, and spatial analysis across industries such as urban planning, environmental management, and transportation. The role often requires skills in programming, data analysis, and tools like Python, R, and GIS software, with strong job growth projected in the coming years.

What are the most commonly searched types of Geospatial Data Scientist jobs in Florida?

The most popular types of Geospatial Data Scientist jobs in Florida are:

What are popular job titles related to Geospatial Data Scientist jobs in Florida?

For Geospatial Data Scientist jobs in Florida, the most frequently searched job titles are:

What job categories do people searching Geospatial Data Scientist jobs in Florida look for?

The top searched job categories for Geospatial Data Scientist jobs in Florida are:

What cities in Florida are hiring for Geospatial Data Scientist jobs?

Cities in Florida with the most Geospatial Data Scientist job openings:

Geospatial Data Scientist jobs near you
Infographic showing various Geospatial Data Scientist job openings in Florida as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $91,721 per year, or $44.1 per hour.

Senior Geospatial Data Scientist/Geospatial AI/ML Scientist

VDart, Inc.

Juno Beach, FL • On-site

Other

Posted 5 days ago

Job description

The Senior Data Scientist Geospatial is a technical leader responsible for designing, developing, and delivering advanced data science, spatial analytics, and machine learning solutions using geospatial data. This role leads complex analytics initiatives, develops scalable analytical applications and spatial data products, establishes technical standards, and mentors junior data scientists and technical team members.

The position partners closely with GIS teams, business stakeholders, and technology leaders to translate complex geospatial and business challenges into scalable, production-ready solutions that deliver measurable business impact.

Key Responsibilities
  • Lead end-to-end data science and geospatial analytics initiatives, from problem definition and data exploration through model development, deployment, and monitoring.
  • Design and develop predictive, prescriptive, and spatial analytics models using large-scale geospatial and enterprise datasets.
  • Architect and deliver scalable GIS tools, analytical applications, spatial data products, and reusable geoprocessing capabilities.
  • Establish technical standards, development frameworks, coding practices, and architectural patterns for enterprise geospatial solutions.
  • Design and oversee spatial data pipelines, APIs, automation workflows, and geoprocessing frameworks.
  • Develop production-grade analytical tools and applications using Python and modern data science technologies.
  • Integrate GIS capabilities with cloud platforms, enterprise data systems, APIs, and AI/ML services.
  • Engineer and optimize features, analytical workflows, and machine learning models for performance, scalability, and reliability.
  • Implement model validation, testing, monitoring, and governance frameworks.
  • Develop automated spatial analysis workflows and reusable geoprocessing components.
  • Collaborate with GIS professionals, data engineers, software engineers, and business leaders to deliver enterprise-level solutions.
  • Translate complex analytical and geospatial findings into clear, actionable recommendations for technical and non-technical stakeholders.
  • Provide technical leadership and mentorship to junior and mid-level data scientists.
  • Evaluate emerging GIS, AI, ML, and data science technologies and recommend solutions aligned with business objectives.
  • Apply strong business acumen and independent problem-solving skills to address complex analytical challenges.
Required Qualifications
  • Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Geography, GIS, Engineering, or another quantitative discipline; advanced degree preferred.
  • 6 10 years of professional experience in data science, analytics, machine learning, or a closely related field.
  • 6 8+ years of relevant experience for senior-level geospatial data science responsibilities.
  • Strong recent experience applying data science techniques to GIS/geospatial problems, preferably within the last 4 years.
  • Strong proficiency in Python or R, with demonstrated experience developing production-ready analytical workflows.
  • Advanced SQL skills and experience working with large-scale datasets.
  • Strong knowledge of statistical inference, machine learning, experimentation design, and predictive modeling.
  • Hands-on experience developing and deploying production-grade models, analytical applications, or data products.
  • Extensive experience with spatial analytics and geospatial data at scale.
  • Strong experience developing enterprise-grade GIS tools, applications, pipelines, and automation workflows.
  • Demonstrated ability to independently lead complex technical initiatives from concept through production.

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