GEOINT Innovation Data Scientist

Leidos•Alexandria, VA

About The Position

The Leidos Geospatial Mission Solutions Portfolio is seeking a GEOINT Innovation Data Scientist to join our team in Alexandria, VA. This is an exciting opportunity to elevate critical national-level missions through innovation, data-driven insight, and advanced analytic solutions. As a GEOINT Innovation Data Scientist, you will help shape the next generation of geospatial capabilities by applying data science to real-world intelligence challenges, with a strong emphasis on machine learning (ML) and natural language processing (NLP) in support of NextGen FMI AI efforts. This position straddles the worlds of direct customer mission support and Leidos-driven innovation, blending hands-on problem solving with forward-looking solution development. We’re looking for someone who thrives at the intersection of geospatial analysis, Python-based development, and applied machine learning, and who is passionate about transforming geospatial data into actionable intelligence that drives smarter decisions and stronger outcomes. High-performing geospatial analysts with strong technical coursework or demonstrated experience in Python, machine learning, or NLP are encouraged to apply. Staffing Requirement The work requires staff to provide the customer with data science and automation support. Staff will collect, process, and perform data analysis and deliver data driven solutions to quantitatively improve multiple mission areas. They will design and develop solutions to complex problems using applied statistics, machine learning techniques, and algorithm development, while collaborating with teammates and customers to translate complex findings into mission-relevant insights. Any data management solutions created should take into consideration modernization objectives, including AI-enabled workflows, modernized database applications, and enterprise-level integration.

Requirements

Strong geospatial experience, including hands-on work with geospatial data, coordinate systems (latitude/longitude, UTM), projections, and data transformations.
5 – 7 years of demonstrated programming experience, with strong proficiency in Python for data analysis, automation, and model development.
3–5 years of experience in data science, including data collection, processing, exploitation, transformation services, modeling, and analytics.
Prior experience in customer footprint supporting analytic production.
Demonstrated experience applying machine learning techniques and/or natural language processing (NLP) to real-world problems.
Experience working with geospatial data in data science or analytic workflows.
Knowledge and experience using version control tools such as Git.
Knowledge and experience using GIS tools such as QGIS and/or ArcGIS.
Knowledge and experience using PostgreSQL, PostGIS, PgAdmin.
Knowledge and experience using APIs.
Knowledge and experience using applied statistics and building algorithms.
Ability to present technical findings clearly to non-technical stakeholders.
Willingness to provide sample code portfolios (e.g., GitHub or similar) demonstrating technical capabilities in Python, data science, ML, or NLP (no proprietary or classified material).
Requires a BA degree and 4 – 8+ years of prior relevant experience or Masters with 2 – 6+ years of prior relevant experience.

Nice To Haves

Experience applying machine learning and/or NLP specifically to geospatial or intelligence problems.
Experience transitioning from geospatial analysis into data science or AI/ML-focused roles.
Experience in combining digital cartography, computer technology, GIS, cartographic and geospatial production techniques, remote sensing, photography, and digital data formats.
Experience performing data analysis to identify trends, anomalies, and opportunities within complex datasets.
Knowledge of ESRI tools including ArcGIS/ArcPro and Arc Server.
Knowledge of database systems and architecture.
Ability writing SQL and NoSQL.
Understanding of cloud architecture, infrastructure, services (including geospatial-specific microservices), and DevOps.
Experience working with geospatial data in multi-user enterprise environments.
Experience analyzing existing production systems and recommending enhancements to enable AI/ML and data science capabilities.

Responsibilities

Provide GEOINT/Data Science expertise to assure continuity of data provision to analytical users.
Statistical analysis, machine learning modeling, and NLP-driven analysis of structured and unstructured data.
Automating repetitive data management and analytic workflows using Python.
Clean, convert, migrate, and organize structured and unstructured geospatial and text-based data.
Perform ad hoc analysis and present results in a clear manner.
Communicate complex quantitative and ML-driven analysis in a clear, precise, and actionable manner using storytelling/visualization. This may include data visualization of disparate sources via dashboards that can be understood by non-technical audiences.
Create/deploy/maintain tools to extract features, data, and metadata from a variety of sources, including rasters, vectors, text, and other source databases.
Write/maintain Python scripts for various environments and software including ArcGIS to improve efficiency of the production process and enable AI/ML workflows.
Deliver service solutions that integrate best practices to modernize current practices, including AI-enabled and NLP-driven analytics.
Perform data investigations on complex problems using applied statistics, machine learning, and algorithm development while collaborating with domain experts.
Ensure new workflows can be integrated seamlessly with modernized database applications and enterprise-level APIs.
Data visualization of production metrics of in-house created data.