Geospatial Data Scientist - Remote

58m58 minutes ago

Leidos

US · Full-time · $85,150 – $153,925

About this role

The Leidos Health and Civil Sector seeks a Geospatial Data Scientist with expertise in machine and deep learning for geospatial applications and snow remote sensing. This role joins the growing Earth Intelligence team with demonstrated funding success across multiple agencies. It leverages resources of a Fortune and S&P 500 company with over 47,000 employees.

The work focuses on building applied scientific tools for federal agencies like NASA, NOAA, USGS, and USACE. It covers the full project lifecycle from proposal and prototyping to customer feedback, revision, and delivery of quality-controlled software. Specific efforts include optical and microwave remote sensing of snow and ice.

This full-time position offers a remote work location anywhere in the US. The incumbent works on multiple projects across federal contracts. Collaboration occurs within a team supported by extensive company resources.

Opportunities involve contributing to high-impact Earth intelligence applications. The role supports ongoing funding success and diverse agency partnerships. It enables development of advanced geospatial tools with real-world federal applications.

Requirements

English language fluency
US Citizen or Permanent Resident
Ph.D. in a technical field involving Earth observations or MSc with 4 years of relevant experience in geospatial data analysis and machine learning
Knowledge of satellite-based or airborne remote sensing instruments including hyperspectral, multispectral, passive microwave, and thermal infrared
Proficiency with machine and deep learning techniques like neural networks and random forests using Python libraries such as scikit-learn, PyTorch, TensorFlow, Keras
Proficiency with Python for processing large geospatial datasets using rasterio, xarray/rioxarray, geopandas, satpy, Dask
Experience with geospatial tools like GDAL, ArcGIS Pro, QGIS and raster data handling including projections and interpolation
Established record of technical writing for proposals, reports, and user manuals

Responsibilities

Build applied scientific tools for federal agencies including NASA, NOAA, USGS, and USACE
Manage full project lifecycle from proposal, prototyping, customer feedback, revision, and delivery of quality-controlled software
Develop machine and deep learning models for geospatial applications and snow remote sensing
Process and analyze large geospatial datasets using Python libraries like rasterio, xarray, and geopandas
Apply remote sensing methods such as hyperspectral, multispectral, passive microwave, and thermal infrared
Work on optical and microwave remote sensing of snow and ice