The federal government is one of the organizations most in need of data scientists, but hiring freezes, slashed training budgets and a lack of qualified candidates have all hampered the ability to recruit these types of professionals. Faced with such obstacles, agencies have been developing creative solutions to fill the hiring gap. Learn how to overcome these challenges with big data analytic tools.

1. The Need for Self-Service Data Tools, Not Scientists
Data science is one of today’s hottest fields and one that is rife with competition. Projections
indicate that employer demand requires that the United States increase the number of graduates
with skills handling large amounts of data by as much as 60 percent.1
Dozens of graduate and
certificate programs are springing up in big data,2
as are digital badge programs which recognize
computer science skills gained in various learning environments.3
The federal government is one of the organizations most in need of data scientists, but hiring
freezes, slashed training budgets and a lack of qualified candidates have all hampered the ability
to recruit these types of professionals. Faced with such obstacles, agencies have been developing
creative solutions to fill the hiring gap.
What Is a Data Scientist?
A data scientist must be extremely well-rounded. Knowing what to look for in the data, finding
it, and conveying discoveries to stakeholders each require a different skill set. As such, data
scientists should have an understanding of almost everything within the realm of data, including
a background in mathematics, programming and tools like Hadoop that organize big data.
Increasingly, data visualization is also being added to this skillset. The best data scientists also
tend to be curious thinkers who thrive in both structured and unstructured environments. Given
the necessary requirements, it is no surprise that data scientists are in short supply.
The Need for Federal Data Scientists
Given recent investments in big data, government has an enormous need for data scientists. The March
2012 Big Data Research and Development Initiative invested $200 million in technology projects aimed
at expanding government’s analytic tools and techniques.4
Data analytics was also one of the seven
priority IT reinvestment areas mandated by OMB during the FY 2014 budget proposal process.5
This investment has a good purpose. Analytics use in government is widespread, but many of
data’s additional benefits have yet to be unlocked. Agencies use data for performance tracking,
goal setting, and improving customer service. With regard to financial management, data can
be leveraged for forecasting and to detect fraud, waste and abuse. Finally, data is important to
government’s cybersecurity posture. Analytics can assist in conducting threat and vulnerability
assessments and in detecting anomalies in network usage.
New mandates are also putting pressure on federal agencies to organize their data. Creating
accessible and open data is a priority of the Obama Administration, exhibited by the establishment
of the Open Data Policy in May 2013. This policy “advances the management of government
information as an asset” by requiring that new and modernized government information resources
exist in open and machine-readable formats. Open data has even become an international
issue. During the June 2013 summit in Northern Ireland, all G8 members agreed to make their
A Briefing
from GBC:
Industry Insights
July 2013
Given recent
investments in big
data, government has
an enormous need for
data scientists.
“
”

2. government data open by default.6
“The world is witnessing the growth of a global movement
facilitated by technology and social media and fuelled by information – one that contains
enormous potential to create more accountable, efficient, responsive, and effective governments
and businesses, and to spur economic growth.”7
Overcoming Obstacles
Despite the need for more data scientists, the federal government has difficulty attracting the right
people for the job. Though educational and for-profit institutions are working to increase the supply
of data science graduates, they are still rare. Those that do meet the necessary criteria are often
lured to high salaries that are more common in the private sector. Even if qualified candidates are
interested in working for the federal government, hiring freezes can make recruitment impossible.
Though government may be unable to hire the people it needs, creative solutions may be available.
One option is for agencies to outsource their data processing, sending some or all of their analytic
needs to outside parties. Outsourcing can be cheaper than hiring more internal employees, especially
if there are multiple companies competing to provide the needed service. It can also reduce fixed
costs, by eliminating the need for investment in expensive equipment. Despite the cost argument,
outsourcing may not be the best choice for federal agencies. Outsourcing of any kind means that the
agency will have less managerial control. For federal agencies dealing with sensitive national security
secrets and personally identifiable information, a demonstrated record of data security and privacy is
essential. Many organizations feel that it is better to keep their data in-house.
Building a Data Strategy
Keeping data analytics capabilities in-house does not mean that agencies have to make do with what
they currently have. Vendors are developing new technologies to make up for the skills gap. In lieu of
hiring more data scientists, agencies can leverage these tools to solve their big data needs.
One such solution, Kitenga Analytics Suite from Dell, has the ability to create reusable content
mining solutions for structured, semi-structured and unstructured data. Kitenga searches for
named entities, such as fraudulent Medicare providers or specific diseases reported, within
documents, tweets, social media posts, and many other kinds of content. The software converts all
data into a searchable format complete with visualizations, empowering non-technical staff to step
into the role of data scientist. Without hiring new employees or involving third parties, tools like
Kitenga help agencies bridge the gap between existing data and actionable intelligence.
Sources:
1. James Manyika, Michael Chui, Brad Brown, Jacques Bughin, Richard Dobbs, Charles Roxburgh and Angela Hung
Byers. “Big Data: The Next Frontier.” McKinsey Global Institute. May 2011. http://www.mckinsey.com/insights/
business_technology/big_data_the_next_frontier_for_innovation.
2. Claire Cain Miller. “Data Science: The Numbers of Our Lives.” New York Times. 11 April 2013. http://www.
nytimes.com/2013/04/14/education/edlife/universities-offer-courses-in-a-hot-new-field-data-science.
html?pagewanted=all&_r=0.
3. Thomas Kalil. “We the Geeks: Building a 21st Century Resume.” Office of Science and Technology Policy. 19 June
2013. http://www.whitehouse.gov/blog/2013/06/19/we-geeks-building-21st-century-resume.
4. Office of Science and Technology Policy. “Obama Administration Unveils “Big Data” Initiative: Announces $200
Million In New R&D Investments.” Executive Office of the President. 29 March 2012. http://www.whitehouse.gov/
sites/default/files/microsites/ostp/big_data_press_release_final_2.pdf
5. Guidance on Exhibits 53 And 300 – Information Technology and E-Government. 2012. http://www.whitehouse.
gov/sites/default/files/omb/assets/egov_docs/fy14_guidance_on_exhibits_53_and_300.pdf.
6. Open Data Charter. 18 June 2013. https://www.gov.uk/government/publications/open-data-charter.
7. Open Data Charter. 18 June 2013.
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About GBC: Industry
Insights
GBC: Industry Insights, a division of
the Government Business Council
and Government Executive Media
Group, is dedicated to advancing
the business of government through
analysis and insight. GBC: Industry
Insights partners with industry
to share best practices with top
government decision-makers,
understanding the deep value
inherent in industry’s experience
engaging and supporting federal
agencies. Contact Dana Grinshpan,
Research Manager, Government
Business Council, at dgrinshpan@
govexec.com.