LMI is seeking a skilled Energy Data Analytics Lead focused on infrastructure, energy, and environment data and tools. Successful candidates demonstrate competency in data pipelining, data analysis, statistics, programming, project execution, tool development and optimization, and critical thinking paired with functional knowledge of infrastructure, energy, or environment data.
LMI is a consultancy dedicated to powering a future-ready, high-performing government, drawing from expertise in digital and analytic solutions, logistics, and management advisory services. We deliver integrated capabilities that incorporate emerging technologies and are tailored to customers’ unique mission needs, backed by objective research and data analysis. Founded in 1961 to help the Department of Defense resolve complex logistics management challenges, LMI continues to enable growth and transformation, enhance operational readiness and resiliency, and ensure mission success for federal civilian and defense agencies. We believe government can make a difference, and we seek talented, hardworking people who share that conviction.
LMI has been named a 2024 #BestPlacestoWork in the United States by Built In! We are honored to be recognized as a company that values a people-centered culture, and we are grateful to our employees for making this possible!
This candidate will join a high-performing team primarily supporting the General Services Administration (GSA) while leading additional data engineering efforts spanning the Infrastructure, Energy, and Environment (IEE) sub-service line. The candidate will optimize existing data pipelines for efficiency, strategize how to transform pipelines for a long-term and scalable data pipeline solution, and build new tools to support a new reporting program.
The candidate will serve as the lead data architect for all tool development, solution implementation, and innovation generation across the division, so a working knowledge of functional IEE considerations is required.
Specific responsibilities include:
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