1

Geopandas Python Jobs in Ohio (NOW HIRING)

$140 - $190/hr

Strong Python programming skills with hands-on experience using geospatial libraries such as GDAL, Rasterio, Shapely, Fiona, and GeoPandas. * Experience with scientific Python tools including NumPy ...

Experience automating workflows using scripting languages, preferably Python (for example, GeoPandas and related libraries). * Familiarity with visualisation and reporting tools such as Power BI or ...

Experience automating workflows using scripting languages, preferably Python (for example, GeoPandas and related libraries). * Familiarity with visualisation and reporting tools such as Power BI or ...

Geopandas Python information

What is GeoPandas in Python?

GeoPandas is an open-source Python library that simplifies working with geospatial data. It extends the popular Pandas library to enable spatial operations on geometric types, such as points, lines, and polygons. With GeoPandas, users can easily read, write, and manipulate geographic data formats like Shapefile, GeoJSON, and others. It integrates well with other libraries, such as Matplotlib for visualization and Shapely for advanced geometric operations, making it a powerful tool for geographic data analysis in Python.

What are the key skills and qualifications needed to thrive as a Geopandas Python developer?

To thrive as a Geopandas Python Developer, you need a solid foundation in Python programming, geospatial data analysis, and GIS concepts, often backed by a degree in computer science or geography. Familiarity with Geopandas, Shapely, Fiona, and other geospatial libraries, as well as experience with spatial databases and data visualization tools, is typically required. Strong problem-solving skills, attention to detail, and effective communication help you deliver robust geospatial solutions and collaborate with team members. These skills are critical for accurately processing spatial data, generating valuable insights, and supporting data-driven decision-making in various industries.

What are some common challenges Geopandas Python developers face when working with large geospatial datasets?

Geopandas Python developers often encounter performance limitations when processing very large geospatial datasets, as Geopandas is built on top of Pandas and can be memory-intensive. Handling operations like spatial joins, dissolves, or aggregations on millions of features may lead to slowdowns or memory errors. To address these challenges, developers frequently use techniques such as chunking data, leveraging Dask for parallel computing, or integrating with more scalable libraries like PostGIS or PyGEOS. Collaborating closely with data engineers and GIS specialists can also help optimize workflows and ensure efficient data processing.

What is the difference between Geopandas Python vs GIS Analyst?

AspectGeopandas PythonGIS Analyst
Required CredentialsPython programming, GIS fundamentalsGIS certifications, degree in geography or related field
Work EnvironmentData analysis, scripting, codingMap creation, spatial data management, report generation
Industry UsageData science, software development, geospatial analysisUrban planning, environmental management, government agencies

Geopandas Python focuses on spatial data analysis using Python programming, ideal for data scientists and developers. GIS Analysts work with spatial data in various industries, often using GIS software and tools. While both roles involve geospatial data, Geopandas Python emphasizes coding and automation, whereas GIS Analysts focus on data management and visualization.

What are popular job titles related to Geopandas Python jobs in Ohio?

For Geopandas Python jobs in Ohio, the most frequently searched job titles are:

Senior Geospatial Machine Learning Engineer

Jobgether

On-site

$140 - $190/hr

Other

Posted 8 days ago


Job description

We are seeking a Senior Geospatial Machine Learning Engineer to develop advanced AI solutions that transform satellite and environmental data into actionable insights.
This role sits at the intersection of machine learning, geospatial technology, and climate innovation, helping solve complex challenges impacting critical infrastructure.
You will work on building and improving algorithms that analyze vegetation, assess risks, and support smarter decision-making for energy systems.
The position offers the opportunity to own impactful projects from experimentation through production while collaborating with multidisciplinary engineering and scientific teams.
You will contribute to the evolution of data-driven products using cutting-edge ML techniques, remote sensing data, and geospatial technologies.
This is an ideal opportunity for an experienced engineer passionate about applying AI to create meaningful environmental impact.

Accountabilities:

The Senior Geospatial Machine Learning Engineer will design, develop, and improve machine learning solutions that leverage geospatial data to deliver innovative environmental intelligence products. This role requires strong technical ownership, collaboration, and the ability to translate complex data challenges into practical solutions.

  • Develop new geospatial intelligence products using Python-based geospatial libraries, machine learning, and deep learning techniques.
  • Improve existing solutions through data exploration, model optimization, debugging, and performance enhancements.
  • Work with satellite and aerial imagery, raster and vector datasets, and geospatial workflows to solve real-world challenges.
  • Lead technical projects from planning and experimentation through implementation, delivery, and stakeholder communication.
  • Build tools and processes to evaluate model performance, product impact, and data-driven prioritization.
  • Collaborate with data engineering, product, platform, and delivery teams throughout the full machine learning product lifecycle.
  • Contribute to technical direction, engineering practices, and team culture within a fast-growing environment.
  • Communicate complex technical concepts clearly to both technical and non-technical stakeholders.
Requirements:

The ideal candidate is an experienced machine learning or geospatial engineer with strong expertise in Python, scientific computing, and applied AI. They should be comfortable working independently, leading projects, and applying advanced technology to environmental and infrastructure challenges.

  • 8–10+ years of experience in machine learning engineering, geospatial engineering, remote sensing, or a closely related technical field.
  • Strong Python programming skills with hands-on experience using geospatial libraries such as GDAL, Rasterio, Shapely, Fiona, and GeoPandas.
  • Experience with scientific Python tools including NumPy, SciPy, scikit-learn, and Pandas.
  • Practical experience developing deep learning solutions using frameworks such as PyTorch and/or TensorFlow.
  • Strong understanding of satellite imagery, aerial imagery, and geospatial raster/vector data processing.
  • Experience with workflow orchestration tools such as Dagster or similar platforms.
  • Ability to independently lead initiatives, manage technical projects, and communicate results effectively.
  • Passion for climate technology and using machine learning to address complex environmental problems.

Nice-to-have qualifications:

  • Experience with vegetation science, forestry, energy infrastructure, or utility-related technologies.
  • Familiarity with observability tools such as Sentry and Grafana.
  • Previous experience in climate tech, geospatial AI, remote sensing, or environmental data companies.
Benefits:
  • Fully remote work environment with flexibility across eligible locations.
  • Opportunity to work on impactful climate technology projects using AI and satellite data.
  • Ability to influence technical direction, processes, and product development within a growing organization.
  • Collaboration with a diverse international team across engineering, product, design, and platform functions.
  • Exposure to cutting-edge machine learning, geospatial technologies, and real-world applications.
  • Inclusive culture focused on solving meaningful problems through technology.
  • Opportunity for professional growth in a mission-driven environment.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

#J-18808-Ljbffr