We are seeking a Senior Supply Chain Data Scientist with demonstrated expertise in modeling, analytics, and spares (D200A/ESCAPE/WSMIS/SAM/D035) to support U.S. Air Force sustainment and supply chain operations. The ideal candidate blends operational supply chain knowledge with advanced analytical and data science capabilities, enabling the development of actionable insights for enterprise-level decision-making. The position supports weapon systems sustainment and will provide strategic recommendations to the USAF sustainment enterprise. This position offers the opportunity to lead high-impact modeling initiatives, deliver innovative analytics, and provide strategic guidance on supply chain policy, readiness modeling, and operational improvement. This position cannot be supported remotely.

LMI is a new breed of digital solutions provider dedicated to accelerating government impact with innovation and speed. Investing in technology and prototypes ahead of need, LMI brings commercial-grade platforms and mission-ready AI to federal agencies at commercial speed. Leveraging our mission-ready technology and solutions, proven expertise in federal deployment, and strategic relationships, we enhance outcomes for the government, efficiently and effectively. With a focus on agility and collaboration, LMI serves the defense, space, healthcare, and energy sectors—helping agencies navigate complexity and outpace change. Headquartered in Tysons, Virginia, LMI is committed to delivering impactful results that strengthen missions and drive lasting value.

• Examine new initiatives and existing processes for opportunities and propose enhanced tools, policies, and procedures.
• Be able to perform or support Readiness-Based Spares modeling on an as needed basis.
• Able to identify and discern problem areas and provide solutions to the client on a recurring basis.
• Be able to articulate technical concepts to non-technical audiences on a recurring basis.
• Identify solutions and provide recommendations on government proposed new capabilities and assist in the transition to other supply systems as necessary.
• Participate in working groups and process improvement teams.
• Develop tools, policies, and procedures to provide the capabilities required for AFSC’s enterprise-level management of the supply chain.
• Develop procedures and supporting tools for assessing the availability impact of limited funding and executing procurement and repair with limited funding.
• Recommend changes and any corrections to regulations, programs, procedures, processes, and testing to prevent recurrence of data quality problems.
• Support projects analyzing existing system-support supply chains (including, inventory management, maintenance, and distribution) in government organizations like the United States Air Force.
• Support projects that re-design or enhance system-support via supply chains.

MINIMUM QUALIFICATIONS:

• Bachelors degree in Mathematics, Industrial Engineering, Operations Research, Supply Chain Management, or a related degree
• Minimum of 10 years of DoD Supply Chain Analytics or Logistics Engineering experience
• Extensive knowledge of USAF modeling, analytics, and spares systems (D200A/ESCAPE/WSMIS/SAM/D035)
• Expert knowledge in computing Fleet Availabilities including Redundancy and Spares
• Familiarity with advanced analytic techniques to include ML algorithms such as Neural Nets
• Ability to acquire a US government clearance (Secret or higher) required.  Must be a US citizen.

PREFERRED QUALIFICATIONS:

• Masters degree in Mathematics, Industrial Engineering, Operations Research, Supply Chain Management, or a related degree
• Minimum of 15 years of DoD Supply Chain Analytics or Logistics Engineering experience
• Familiarity with FORTRAN, VBA, MS Office Tools, R, Python, Tableau, PowerBI, SAS
• Current or ability to acquire a Top Secret US government clearance

Targeted Salary Range: $100,000 - 155,000

Disclaimer:

The salary range displayed represents the typical salary range for this position and is not a guarantee of compensation. Individual salaries are determined by various factors including, but not limited to location, internal equity, business considerations, client contract requirements, and candidate qualifications, such as education, experience, skills, and security clearances.

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