Senior Data Scientist (SOM) - TS/SCI cleared

Leidos•Springfield, VA

About The Position

Leidos has an exciting opportunity for a Senior Data Scientist (SOM) to join our growing team in Springfield, VA. In order to be considered you must have an active TS/SCI clearance. This unique and challenging opportunity will require our talented staff to collect, process, and perform data analysis and deliver data-driven solutions to quantitatively improve the mission area of Maritime Features, Surface, Publications, Events, Dissemination, Source Assessment, and Metrics. Primary Responsibilities Apply Structured Object Management (SOM) principles (points, lines, polygons) to organize and manage geospatial data. Structure disparate and unstructured data into usable formats for quantitative analysis and multi-source data fusion. Develop and implement automated workflows and data pipelines to enhance analytic production and efficiency. Design and maintain ontologies and data schemas to standardize data across systems and analytic efforts. Utilize Python, R, or SQL to develop, optimize, and maintain analytic pipelines and data workflows. Provide GIS support, including advanced use of ArcGIS Pro (ArcPro) for analysis, visualization, and data management. Collect process data and perform data analysis. Integrate centralized protect and maintain data in DBMS. Clean massage and organized data. Perform ad hoc analysis and present results in a clear manner. Communicate complex quantitative analysis in a clear, precise and actionable manner using storytelling/visualization. Create/deploy/maintain cloud applications to support migration of data and production processes Create/deploy/maintain tools to extract features data and meta-data from a variety of sources, including Raster to vector-to-vector text to vector and text database. Write/maintain Python scripts in Arc GIS to improve efficiency of the production process. Support Business Processing Re-engineering. Perform Data Conversion/migration Perform Business Analytics.

Requirements

Typically requires a BA degree and 8 – 12 years of prior relevant experience or Master’s with 6 – 10 years of prior relevant experience.
Must have active TS/SCI clearance
5 – 7 years of demonstrated programming skills with the ability to write/maintain scripts, including Python and JAVA scripts.
Knowledge and experience using version control tools such as Git.
3–5 years’ experience in data science, including data collection, processing, exploitation, transformation services, modeling, and analytics.
3–5 years of demonstrated experience performing geospatial data management, including data type conversions, coordinate systems (latitude/longitude, UTM), and projections.
1 – 3 years of experience using Tableau or equivalent Business Intelligence software and server functions.

Nice To Haves

Experience combining digital cartography, GIS, remote sensing, and geospatial production techniques.
Proficiency in Feature Manipulation Engine (FME) software such as FME Workbench.
Experience performing data analysis to identify trends, gaps, and opportunities.
Knowledge of ESRI technologies including ArcGIS, ArcPro, and Arc Server.
Experience with ESRI Workflow Manager (WMX/TAM).
Knowledge of database systems and architecture.
Ability to write SQL and NoSQL.
Understanding of cloud architecture, infrastructure, services, and DevOps.
Knowledge of symbolization rules.
Familiarity with emerging AI technologies and their integration into geospatial workflows.
Experience working with geospatial data in multi-user enterprise environments.
Experience with data quality control tools such as ArcGIS Data Reviewer.
Experience analyzing production systems and recommending enhancements to data science capabilities.
Active TS/SCI CI Poly

Responsibilities

Apply Structured Object Management (SOM) principles (points, lines, polygons) to organize and manage geospatial data.
Structure disparate and unstructured data into usable formats for quantitative analysis and multi-source data fusion.
Develop and implement automated workflows and data pipelines to enhance analytic production and efficiency.
Design and maintain ontologies and data schemas to standardize data across systems and analytic efforts.
Utilize Python, R, or SQL to develop, optimize, and maintain analytic pipelines and data workflows.
Provide GIS support, including advanced use of ArcGIS Pro (ArcPro) for analysis, visualization, and data management.
Collect process data and perform data analysis.
Integrate centralized protect and maintain data in DBMS.
Clean massage and organized data.
Perform ad hoc analysis and present results in a clear manner.
Communicate complex quantitative analysis in a clear, precise and actionable manner using storytelling/visualization.
Create/deploy/maintain cloud applications to support migration of data and production processes
Create/deploy/maintain tools to extract features data and meta-data from a variety of sources, including Raster to vector-to-vector text to vector and text database.
Write/maintain Python scripts in Arc GIS to improve efficiency of the production process.
Support Business Processing Re-engineering.
Perform Data Conversion/migration
Perform Business Analytics.