Data Scientist

Job ID
# of Openings Remaining
Residency Status
No Restrictions
No Clearance Required
Employee Type
Time Type
Full Time


Vencore Labs (formerly Applied Communication Sciences) is a self-sustaining research center within Vencore that provides applied research and engineering to enable government agencies, utilities and commercial enterprises to fully exploit the future of communications, data analytics and cyber security. From smart grid to smart phones, intelligent highways to intelligent battlefields, Vencore Labs’ 200 scientists, engineers and analysts are consistently creating generation-after-next technologies and solutions.  In doing so, our labs are helping to transform traditional government research.  We connect our customers to advanced research and technology helping them to develop solutions to their toughest challenges.  Accelerating the arc of transformation — from research to engineering to products — that’s what we focus on each day at Vencore Labs.


We offer very competitive salaries, annual bonuses, and a 5% dollar for dollar 401k match which is immediately fully vested, among other benefits. But the thing that our employees consistently cite as their favorite things about working here are: (1) the extremely interesting and varied nature of the work, which is cutting edge research; and (2) the extremely high caliber of their co-workers. Many of our employees are experts in their fields and work very collaboratively with their colleagues. Vencore Labs routinely partners with government, top-tier colleges and universities, and other companies in the industry to research and develop innovative technology solutions.  

Vencore is an AA/EEO Employer - Minorities/Women/Veterans/Disabled


Description of the project: The demand for analysis of data sets, data analytics and text analytics is growing with the expanding streams of available data.  The projects are designed to provide enterprise analysis, analytical software, tools, dashboards, reports and analytical data support to the customer, all based on the methods and models developed by financial economists.


Minimum qualifications:

  • Master’s degree in computer science, statistics, or applied mathematics
  • 4 years' experience in creating machine learning pipelines to derive insights from data (i.e., from data aggregation and cleaning, to using machine learning techniques)
  • Familiarity with unsupervised (e.g., clustering), semi-supervised (e.g., label propagation), and supervised learning (e.g., ensemble classifiers) algorithms, and when it is appropriate to use each
  • Deep experience in creating, managing, and analyzing large datasets
  • Familiarity with contemporary scripting languages such as Python and R, the Hadoop computational ecosystem, Oracle relational databases, and the Linux/UNIX operating system


Preferred qualifications:

  • Knowledge of deep learning paradigms and architectures


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