Defining the Roles, Responsibilities, and Functions for Data Science Within the Defense Intelligence Agency
by Bradley M. Knopp, Sina Beaghley, Aaron B. Frank, Rebeca Orrie, Michael Watson
This report addresses and recommends potential methods for the Defense Intelligence Agency (DIA) to identify, hire, and organize data scientists. The authors examine data science activities in the private sector and university-level data science training and also explore hiring and retention options for creating a data science capability within DIA. They also examine the results of interviews with DIA employees. The authors recommend that DIA create its own data science capability with a mix of government experts and contractors capable of managing activities unique to military intelligence operations and that DIA establish a center of excellence to oversee and promote data science activities, development, and training.
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Key Findings
Collaboration is essential to data science.
DIA must decide on what it wants to achieve through data science. It must decide whether to have an organic data science capacity or acquire data science products from outside.
DIA must also figure out the workforce skills it needs to achieve the desired output. It would be sensible to employ contract personnel, government civilians, and active-duty military personnel to ensure the broadest representation of technical skills and subject-matter expertise.
Training managers and leaders will be critical to embedding data science into the organization.
Recommendations
DIA should build a data science capability with a mix of government experts and contractors capable of managing activities unique to military intelligence operations.
DIA should establish a center of excellence or other centralized body to coordinate data science activities; develop tradecraft and methodologies; promote projects; and advocate for resources, support, and training.
A combination of contractors and government civilians/active-duty military will allow DIA to build an agile workforce with fungible capabilities.
DIA will need to establish a training structure for data science.
DIA should establish a Data Science Roundtable to achieve the internal cultural changes to ensure data science is an enduring agencywide capability.
Table of Contents
Chapter One
Introduction
Chapter Two
Data Science Activities in the Private Sector
Chapter Three
Data Science Education
Chapter Four
Identifying and Defining Data Science Specialties
Chapter Five
Data Science Capability in DIA Today
Chapter Six
Building and Maintaining a Data Science Capability
Chapter Seven
Organizing Data Science at DIA
Chapter Eight
Building DIA’s Data Science Capability: Findings and Recommendations
Appendix A
Interview Protocol
Appendix B
Notional Data Science Position Descriptions
Appendix C
Methodology
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