Data Analyst (Hybrid Remote)
TECHEAD
Posted 1 day ago
Hire Military
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About the Company: CANA LLC (CANA) is a purpose-driven firm that applies analytics-based logistics solutions for Federal/State U.S. Government and commercial clients. CANA’s principles include integrity, quality, best value, and respect. We believe that a better quality of life is achievable. The science around and application of quantitative methods can make a difference. Our brand, Powered by CANA Analytics®, refers to our CANA professionals and our solutions. It is the power of having subject matter experts who can deliver a fusion of information to our clients. This includes applied analytics methods, software development, supply chain and logistics operations, warehousing, program and project management, energy infrastructure and mobility planning, and logistics systems integration. Role Summary: The CANA Senior AI Data Analyst is an adept leader in the Commercial and/or Federal analytics community. This is a senior technical position that requires a broad range of application experience, knowledge, and abilities to work independently and with a group, and to provide leadership through projects and tasks. This is a hybrid position; the on-site work will be within the Pentagon in support of Logistics Plans (LP) Division, Headquarters Marine Corps. Anticipated start date for this role is between 30 October 2026 and 1 December 2026. Position is contingent on contract award. Duties and Responsibilities: The Senior AI Data Analyst will be a proven leader in the analytics community - commercial and/or Federal sectors. They will provide ethically derived analytical results to support high-impact decisions by CANA clients. The Senior AI Data Analyst will present themselves and their work professionally and represent CANA with the utmost pride in working group settings, professional forums, with CANA clients, and all company (internal and external) interactions. They have the ability to communicate at all management and technical levels - understanding and adapting appr
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