Systems Planning and Analysis, Inc. (SPA) is a well-established and progressive defense contracting company headquartered in the Northern Virginia area just a few miles south of the Pentagon. We are a professional services firm established in 1972 that has a long-standing reputation for unrivaled technical and analytical support to some of the top decision makers in the Federal Sector. We do state of the art work and have a cadre of outstanding professionals on our team.
SPA’s Emerging Markets Group is responsible for a broad range of analytical, systems engineering, independent assessments, strategic planning, and technology research, development, testing and evaluation (RDT&E) programs in support of new SPA markets, as well as the company’s San Diego office and portfolio.
SPA has a future need for Data Analysts at junior, mid, and senior levels. Work is expected to begin in FY 2021.
Successful Data Analysts will be responsible for some or all of the following items, depending upon seniority: 1) Collect and organize data, 2) Manage data repositories, 3) Conduct data analysis using established tools, software, and methods, 4) Apply statistical and/or mathematical techniques on data to identify trends, outliers, and correlations, 5) Construct presentations and supporting documentation of findings tailored for specific audiences.
Job responsibilities will also include stakeholder engagement and cross-functional collaboration between various teams toward common goals supporting program execution.
Applicants for mid- and senior-level positions should expect job responsibilities covering more/most of the mentioned areas.
This position will support the program management and systems engineering activities of a U.S. Navy acquisition program office responsible for the development, procurement, and fielding of integrated information technology systems and systems of systems. The applicant will be expected to contribute to the development of recommendations to inform decision-making. Recommendations should be focused on creating efficiencies and increasing program execution effectiveness, using research, data modeling techniques, and data-driven analysis.