Senior Data Scientist Security Clearance

Position: Senior Data Scientist with Security Clearance
Job Title:

Senior Data Scientist Job Category:
Information Technology Time Type:
Full time Minimum Clearance Required to Start: TS/SCI with Polygraph Employee Type:
Regular Percentage of

Travel Required:

None Type of Travel:
None *
*
* The Opportunity:

CACI is seeking a Senior Data Scientist to drive high-impact analytics for the National Geospatial-Intelligence Agency (NGA) in Springfield, VA. In this role, you'll transform complex data into actionable insights, engineer innovative analytical solutions, and shape strategic decision-making across critical NGA programs. Join us to lead advanced data initiatives, integrate cutting-edge tools, and help deliver mission-focused GEOINT capabilities! Responsibilities:
• Provide statistical and mathematical support to analyze and interpret a wide range of data to help NGA understand the value of NGA Programs and support strategic resource decisions made by NGA leadership.

• Interpret and analyze leadership information needs, and design and implement data analysis projects to address those needs by incorporating best practices, appropriate data, and proven techniques from experience or research methods.

• Conduct business analytics tool Architecture and Engineering Analysis to ensure integration of existing and future business analytics tools and compliance with enterprise IT policies, architecture and resources.

• Document, analyze, and (as needed) enhance data conditioning processes that translate raw data inputs into decision-quality data products appropriate to the intended audience.

• Design, develop, test and communicate data analytics products (including data, applications and visualizations) from documented, repeatable methods, based in sound data engineering principles and applicable standards.

• Leverage wide-ranging data sources (e.g., web traffic, customer requests for information, survey data, stated and implied requirements, production databases, human capital data, etc.) to develop and communicate understanding of phenomena and trends to support CAPE studies and assessments.

• Provide insights through repeatable, transparent analysis that will be used to inform NGA strategy and decisions in partnership with teams supporting agency decision making processes, customer and partner interactions, featured content, and future GEOINT products and services.

• Assist in the construction of data sets and data views for use by the CAPE Business Analytics Division to utilize and communicate complex data sets meaningfully and appropriately.

• Assist with implementation of statistical analysis process improvements and incorporation of statistical research into new analytical products and methods.

• Generate and maintain reports, schematics and other documentation sufficient to maintain CAPE Business Analytics Division awareness of data ingest, conditioning and visualization processes as on a regular basis and modify them as required.

• Provide continuous feedback and recommendations to the Business Analytics Division and CAPE.

• Prepare reports, briefings, documents and evaluation of results as required. Specific Deliverables as required:
• Analysis of current and proposed future information systems.

• Data ingest, conditioning and visualization process documentation, including commented scripts and algorithms.

• Database documentation including generation scripts, table and schema definitions, and data definitions.
• Project/Concept Plans.

• Briefings, papers.

• Meeting agendas and minutes.

• Business Analytics architecture & engineering status reports (weekly or as needed).
• Engineering analyses and integration plans (as needed).
• Input for monthly progress reports (monthly).

Qualifications:

Required:

• Bachelor's Degree in Engineering, Computer Science, Mathematics or related quantitative field.

• Minimum 10 years' experience.

• Familiarity with data mining, ability to develop and manipulate, and maintain databases.

• Manipulate, synthesize and visualize large datasets from and between knowledge domains, using appropriate programming languages and software, including but not limited to Semantic Query Language (SQL), Apache Spark, Elastic Search, R, Python, Tableau,…