1

Senior Applied Scientist Machine Learning Jobs in Florida

Build predictive models using statistical and machine learning techniques, with a focus on pricing ... and applied ML roles as business needs evolve * Experience designing and executing pilot ...

New

Machine Learning Engineer

Miami, FL · On-site

$80 - $120/hr

Knowledge of applied mathematics, including convex optimization, quadratic programming, and partial ... in Machine Learning; Experience with deep learning frameworks like TensorFlow or PyTorch;

Job Title Senior Data Scientist Location Doral, FL 33122 US (Primary) Category Intelligence Job ... Possess the knowledge and capability to develop advanced machine learning models and optimize ...

Showing results 21-40

Senior Applied Scientist Machine Learning information

What are the most commonly searched types of Applied Scientist Machine Learning jobs in Florida?

The most popular types of Applied Scientist Machine Learning jobs in Florida are:

What are popular job titles related to Senior Applied Scientist Machine Learning jobs in Florida?

For Senior Applied Scientist Machine Learning jobs in Florida, the most frequently searched job titles are:

What job categories do people searching Senior Applied Scientist Machine Learning jobs in Florida look for?

The top searched job categories for Senior Applied Scientist Machine Learning jobs in Florida are:

What cities in Florida are hiring for Senior Applied Scientist Machine Learning jobs?

Cities in Florida with the most Senior Applied Scientist Machine Learning job openings:

Sophomore Data Scientist Geospatial/Geospatial Machine Learning Scientist

VDart, Inc.

Juno Beach, FL • On-site

Other

Posted 2 days ago

New


Job description

The Sophomore Data Scientist Geospatial supports the design, development, and delivery of analytical and modeling solutions using geospatial data. This role works closely with senior data scientists, GIS teams, engineers, and business stakeholders to analyze complex datasets, develop spatial analytics solutions, and translate geospatial information into actionable business insights.

The position provides hands-on opportunities to develop scalable GIS tools, analytical applications, spatial data products, and reusable geoprocessing capabilities while gaining experience with enterprise geospatial platforms, cloud technologies, and AI/ML services.

Key Responsibilities
  • Support end-to-end data science and geospatial analytics projects, including data preparation, exploration, feature engineering, modeling, testing, and documentation.
  • Develop analytical and machine learning solutions using structured, unstructured, and geospatial datasets.
  • Build and maintain spatial data pipelines, APIs, automation workflows, and geoprocessing tools.
  • Develop reusable GIS tools, analytical applications, and spatial data products to support business and operational requirements.
  • Perform spatial analysis, data visualization, statistical analysis, and predictive modeling.
  • Develop production-ready Python-based analytical workflows and applications under the guidance of senior technical staff.
  • Assist with integrating GIS capabilities with cloud platforms, enterprise data systems, APIs, and AI/ML services.
  • Support the development and optimization of spatial data processing and analytical workflows.
  • Participate in model validation, testing, monitoring, and performance optimization.
  • Collaborate with GIS professionals, data engineers, software engineers, and business stakeholders.
  • Document analytical methodologies, technical solutions, workflows, and results.
  • Communicate analytical findings and recommendations to both technical and non-technical stakeholders.
  • Learn and apply enterprise development standards, geospatial best practices, and modern data science methodologies.
Required Qualifications
  • Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Geography, GIS, Engineering, or a related quantitative field; advanced degree preferred.
  • 2 4 years of professional experience in data science, analytics, machine learning, GIS, or a related field.
  • Experience applying data science techniques to GIS or geospatial problems preferred, particularly within the last 4 years.
  • Strong proficiency in Python and experience developing analytical or data processing workflows.
  • Working knowledge of SQL and experience working with large or complex datasets.
  • Understanding of statistical analysis, machine learning, predictive modeling, and data visualization.
  • Hands-on experience with geospatial data, spatial analytics, or GIS technologies.
  • Ability to develop analytical tools, applications, scripts, and automated workflows.
  • Strong problem-solving, analytical, communication, and collaboration skills.