Data Scientist

Leidos•Alexandria, VA

13d•Onsite

About The Position

Leidos is actively hiring for multiple Data Scientists to support their team in Alexandria, VA. The Data Scientist will support the maintenance and implementation of the data architecture for all Program data. This position requires experience with databases, cloud architecture, and compliance with data standards. The role is responsible for maintaining data backend workflows that allow for the movement of data across security domains and across systems.

Requirements

4+ years of experience working with SQL or NoSQL databases and cloud architectures
Experience leveraging APIs to query systems and migrate data
Excellent written and verbal communication skills
Experience with programming languages such as Python, JavaScript, or Java
Experience developing and sustaining operational data pipelines supporting multiple data formats and interfaces
Bachelor’s Degree in a related field, or equivalent experience

Nice To Haves

Experience working with NGA IT enterprise solutions (e.g., NGA CORE, NGA MLOps)
Experience with Government Authority to Operate (ATO) processes
Experience with Government Non-Person Entity (NPE) certificates
Experience implementing processes, standards, and tools within an organization based on the Scaled Agile Framework for Enterprise
Experience developing dynamic visualizations to monitor availability, currency and volumetrics of operational data pipelines

Responsibilities

Assist in the creation of the necessary data pipelines to store and process data related to emergent sensors and platforms, including database tables and schemas, data health alerts, and ETL setup.
Develop workflows for API-based data movement between data platforms as directed by the government.
Ensure all sensor data adheres to Government-directed data schemas, formats, and governance requirements.
Assess potential differences in metadata, data format, and data structure characteristics in regards to changes to databases, schemas, APIs, and other ETL processes.
Determine how to pre-process and standardize data to match existing data standards or transform it for labeling and model testing, which may include file format conversion, image tiling, orthorectification, or other data manipulation.