REQUIRED QUALIFICATIONS -
1) Active TS/SCI clearance with Poly
2) Requires 12 to 15 years with BS/BA or 10 to 13 years with MS/MA or 7 to 9 years with Ph.D.
3) Domain experience in Intelligence Community (IC), Department of Defense (DoD), or Commercial IT programs
4) Excellent written and oral communication skills, ability to facilitate meetings with multi-organizational stakeholders, understanding explicit and implicit deliverables
5) Self starter, proactive in responding to customer needs, ability to work independently and within team environments
6) Strong attention to detail
7) Ability to relate professionally with customers and colleagues
8) Ability to operate in an extremely dynamic environment
9) Responsible, reliable and flexible
10) Passion for learning and knowledge transfer
11) Ability to work independently or in a team environment, as needed.
DESIRED QUALIFICATIONS -
1) Bachelor or Master degrees in Systems Engineering, Computer Science, Engineering or other Information Technology disciplinesOverview
2) Experience working with Geospatial/GEOINT or SIGINT data/information.
3) Ability to lead and influence
Vencore is a proven provider of information solutions, engineering and analytics for the U.S. Government. With more than 40 years of experience working in the defense, civilian and intelligence communities, Vencore designs, develops and delivers high impact, mission-critical services and solutions to overcome its customers most complex problems.
Headquartered in Chantilly, Virginia, Vencore employs 3,800 engineers, analysts, IT specialists and other professionals who strive to be the best at everything they do.
Vencore is an AA/EEO Employer - Minorities/Women/Veterans/Disabled
Does the idea of working on a devoted team sound appealing to you?
Do you want to work on solving some of our most critical national needs?
Do you want to work on something that will have a long lasting impact to our nation’s security?
LANDMARK Ground Support Services (GSS) Program performs technical planning, systems integration, verification and validation, cost and risk, and supportability and effectiveness analysis for total systems. Analyses are performed at all levels of total system product to include: concept, design, fabrication , test, installation, operation, maintenance and disposal. Ensures the logical and systematic conversion of customer or product requirements into total systems solutions that acknowledge technical, schedule, and cost constraints. Performs functional analysis, timeline analysis, detail trade studies, requirements allocation and interface definition studies to translate customer requirements into hardware and software specifications.
Recognized expert within the company, who designs, researches and develops highly advanced applications, which may result in new product/business opportunities for the company. Leads efforts to capture new business through technical work and capability briefings. The Data Scientist will be involved in the analysis of unstructured and semi-structured data, including latent semantic indexing (LSI), entity identification and tagging, complex event processing (CEP), and the application of analysis algorithms on distributed, clustered, and cloud-based high-performance infrastructures. Exercises creativity in applying non-traditional approaches to large-scale analysis of unstructured data in support of high-value use cases visualized through multi-dimensional interfaces. Handle processing and index requests against high-volume collections of data and high-velocity data streams. Has the ability to make discoveries in the world of big data. Requires strong technical and computational skills - engineering, physics, mathematics, coupled with the ability to code design, develop, and deploy sophisticated applications using advanced unstructured and semi-structured data analysis techniques and utilizing high-performance computing environments. Has the ability to utilize advance tools and computational skills to interpret, connect, predict and make discoveries in complex data and deliver recommendations for business and analytic decisions. Experience with software development, either an open-source enterprise software development stack (Java/Linux/Ruby/Python) or a Windows development stack (.NET, C#, C++). Experience with data transport and transformation APIs and technologies such as JSON, XML, XSLT, JDBC, SOAP and REST. Experience with Cloud-based data analysis tools including Hadoop and Mahout, Acumulo, Hive, Impala, Pig, and similar. Experience with visual analytic tools like Microsoft Pivot, Palantir, or Visual Analytics. Experience with open source textual processing such as Lucene, Sphinx, Nutch or Solr. Experience with entity extraction and conceptual search technologies such as LSI, LDA, etc. Experience with machine learning, algorithm analysis, and data clustering.