1

Geospatial Data Scientist Jobs in Quebec (NOW HIRING)

Data Engineer

Montreal, QC · On-site

  • Retirement

  • PTO

You will partner with Engineers, Product Managers, and Data Scientists to deliver high-quality data ... Experience working with high-volume geospatial, weather, or time-series datasets. * Familiarity ...

Geodata Scientist

Montreal, QC · Remote

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

You will deliver consulting projects focused on prospectivity analysis, geoscience data integration ... Practiced in working with geospatial datasets and spatial analysis workflows. * Strong ...

... science\/ML. \n * Create repeatable reference implementations for common digital product scenarios (IoT telemetry, time series, transactional + event fusion, documents, geospatial). \n Unified Data ...

Experience working with geospatial and remote sensing data formats (e.g., GeoTIFF, GeoJSON, raster/vector data) * Interest in scientific analysis, atmospheric sciences, remote sensing and space ...

Geospatial Data Scientist information

See Quebec salary details

$25.5K

$107K

$168.5K

How much do geospatial data scientist jobs pay per year?

As of Aug 18, 2026, the average yearly pay for geospatial data scientist in Quebec is $107,042.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,500.00 and $123,000.00 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 popular job titles related to Geospatial Data Scientist jobs in Quebec?

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

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

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

Infographic showing various Geospatial Data Scientist job openings in Quebec 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 $107,042 per year, or $51.5 per hour.

Geospatial Data Engineer

Shearwater Aerospace

Montreal, QC • On-site, Remote

Full-time

Re-posted 14 days ago


Job description

We're Building Autonomous Flight Intelligence

Drones that think for themselves. Not pre-programmed routes-true autonomy where aircraft make intelligent decisions onboard, adapting to weather, obstacles, and airspace in real-time without human intervention.

We're building weather-aware flight optimization that delivers outcome-driven autonomy for the real world-increasing mission success by extending range, endurance, safety, and reliability.

You'll architect the geospatial brain that makes this possible

The Opportunity

You'll be our first geospatial hire, building the data processing systems that enable autonomous flight decisions. Working with our CTO, you'll architect how our systems evolve from initial implementation to production-grade infrastructure that handles real-world operational demands.

What you'll own:
  • Design geospatial processing pipelines that balance performance, accuracy, and extensibility
  • Build GIS analysis algorithms for weather-aware route optimization
  • Integrate multi-source datasets (elevation, obstacles, airspace, meteorological models)
  • Create APIs that enable real-time flight decision-making
  • Establish patterns and tooling that evolve as our platform matures

Why this matters: Operators deploy missions in challenging conditions. Your work directly determines whether autonomous systems can navigate safely, optimize for changing weather, and complete objectives-or get grounded.

You Might Be a Fit If...

You think in trade-offs.
You can explain why you chose PostGIS over alternative spatial databases, or when to pre-process vs. compute on-demand. You know the geospatial database landscape and select tools based on requirements, not trends. You're comfortable defending your decisions and pivoting when new constraints emerge.

You stay current and execute rigorously.
You follow modern geospatial best practices and understand OGC standards. You keep up with evolving tools and approaches instead of relying on outdated tooling.

You've shipped production GIS systems.
You've wrestled with coordinate transformations, spatial indexing, and raster processing. You know the common GIS tools and libraries-GDAL/OGR, various spatial databases, processing frameworks-and understand when each fits. Bonus: you've worked with meteorological data (NetCDF, GRIB) or atmospheric models.

You're comfortable with ambiguity.
Requirements evolve. Priorities shift. You ask clarifying questions, propose solutions, and deliver incrementally rather than waiting for perfect specs.

You communicate clearly.
You can explain technical trade-offs to non-engineers and translate vague product needs into concrete implementation plans. Ego doesn't enter the room when someone questions your approach.

Technical Foundation We're Looking For

Core GIS competency:

  • 4+ years building geospatial software (or 3 years if you've shipped impressive systems)
  • Strong knowledge of common GIS tools and libraries (QGIS, GDAL/OGR)
  • Experience with geospatial algorithms (visibility analysis, spatial operations, terrain analysis)
  • Deep understanding of coordinate systems, projections, and spatial data structures

Python ecosystem:

  • Strong Python with scientific computing stack (NumPy, Pandas, SciPy)
  • Geospatial libraries: GeoPandas, Rasterio, Xarray, Dask

Data infrastructure:

  • Experience with spatial databases (PostGIS, Apache Sedona, etc)
  • Comfortable with cloud infrastructure (GCP preferred), Docker, Git
  • Ability to set up automated data ingestion workflows

Nice to have:

  • C/C++ for performance-critical processing
  • Meteorology, atmospheric science, or aviation background
  • Degree in GIS, Computer Science, Engineering, or related field. Master's is a plus, but we'll prioritize what you've built over credentials.
What We Offer

Equity ownership - You're building foundational systems. You should own a meaningful piece of what we're creating.

Architectural influence - This isn't "implement the spec." You'll shape technical decisions alongside the CTO as we define what autonomous flight infrastructure looks like.

Hybrid flexibility - Work where you're most productive. We're in Montreal but value focus time and thoughtful collaboration over face-time.

Growth with the platform - You'll evolve systems as we mature from initial architecture to production-hardened infrastructure. The foundations you establish will scale with increasing mission complexity, data volumes, and operational demands-and you'll architect that evolution.

Direct impact - Your code runs onboard aircraft making critical flight decisions. You'll see your work enable missions that weren't possible before, extending operational capabilities in real-world conditions.

Apply

We're looking for problem-solvers who thrive when building systems from first principles in a domain that matters.

Strong foundation in geospatial engineering but don't check every box? We want to hear from you. We value learning agility and problem-solving ability over credential collection.

Employment Type: FULL_TIME