Imagery Scientist (EO)

Leidos•Alexandria, VA

1d•$92,300 - $166,850•Onsite

About The Position

Leidos is actively hiring for an Imagery Scientist (EO) to join our team in Alexandria, VA. The EO Geospatial Analyst shall provide geospatial and imagery expertise and quantitative analysis to make recommendations that improve data curation and development in support of Machine Learning algorithm testing and evaluation.

Requirements

Experience with Electro-optical imagery analytical products and conducting multi-INT analysis
Utilize structured, unstructured, and semi-structured data and visualization tools to exploit data through use of programming and scripting, including advanced geospatial skills and an excellent understanding of how to apply evolving technology and methodologies to related issues
Bachelor’s Degree in related field. Additional years of experience can be considered in lieu of degree
Active TS/SCI with ability to be approved for a Poly

Nice To Haves

Exhibit experience applying CV and machine learning (ML) techniques to EO imagery and data to address intelligence problems

Responsibilities

Leverage multi-INT data, with an emphasis on EO, to curate imagery from the emergent sensors. Curated imagery will be prioritized for creation of labeled data to support the model evaluation and accreditation. Curated imagery should have objects of interest or needed characteristics (e.g., geographic coverage, scene attributes) per Government prioritization.
Based on the characteristics and limitations of the emergent sensor, recommend curation strategies and identifying data gaps to develop a diverse, representative dataset for Machine Learning model evaluation
Assist the EO lead in conducting assessment of potential differences between new sensor characteristics and capabilities compared to currently utilized platforms
Assess potential differences in metadata, data format, and data structure characteristics in regards to changes to databases, schemas, APIs, and other ETL related processes for the ingestion and movement of data when integrating into the existing data operations pipeline
Determine how to acquire new data, potential latency associated with acquisition, data formats, and security domains
Determine how to pre-process and standardize the data to match existing data standards or to be transformed into a usable state for labeling and model testing purposes. This may involve converting between file format types or tiling full-size images into specified sizes or geospatial bounds.