Geospatial Data Scientist - Remote

1w1 week ago

NV5

US · Full-time · $130,000 – $170,000

About this role

NV5 is seeking an experienced and motivated Geospatial Data Scientist to join a growing team of geospatial, AI, and data science professionals. The role focuses on developing efficient cloud-based geospatial data pipelines and workflows. It supports the US Army Corps of Engineers, requiring U.S. Citizenship and a Department of Defense Common Access Card held within the last two years.

Daily work involves building CI/CD pipelines with integrated unit tests and developing data analytics over spatial and non-spatial big datasets. Professionals comfortable in modern, open-source Python ecosystems will contribute to production-grade analytical tools. Emphasis is on efficient pipelines using libraries like PostgreSQL, DuckDB, and GeoParquet.

This is a fully remote position within an engaged, virtual division at NV5. Travel is less than 10% of the time. Proof of U.S. Citizenship is required for all candidates.

NV5 Geospatial brings together innovative thinkers across engineering, GIS, software development, and more. The team values diversity, collaboration, and care for communities and the environment. Continuous growth expands individual and collective potential in solving tough problems.

Requirements

5 years of experience in data science, geospatial, IT, ML/AI, or related field
Must have held a Department of Defense Common Access Card within the past two years
U.S. Citizenship required
Data/database architecture design within cloud computing infrastructure
Systems analysis
Experience working with geospatial data
Strong Python engineering experience in production systems
Proven ability to design efficient spatial data pipelines

Responsibilities

Translate business requirements into technical specifications, data models, data streams, and databases
Develop production-ready geospatial workflows and data pipelines using open-source Python libraries
Work with OLTP and OLAP stacks including PostgreSQL, DuckDB, PyArrow, Parquet, and GeoParquet
Develop spatial computations with H3, Shapely, GDAL/OGR, and other lightweight geospatial utilities
Write testable, benchmarked code using pytest and async test patterns
Build CI/CD pipelines with integrated unit tests
Embed ML/AI workflows into production-grade enterprise systems
Design, develop, and maintain infrastructure for geospatial analysis and ML/AI applications on large data