The need for Precision Sustainment capabilities arises directly from the demands of future near-peer conflicts and the contested nature of those operational environments. Sustainment Analytics is essential for enabling Predictive Logistics, relying on data-driven solutions to optimize operations. By leveraging advancements in Artificial Intelligence (AI), Machine Learning (ML), and Generative AI, we can enhance sustainment analytics, providing decision-makers with the detailed insights required at all echelons to make informed, data-driven sustainment decisions.

LMI is actively seeking a Sustainment Analytics Subject Matter Expert (SME) to contribute to sustainment modernization efforts. The selected SME will collaborate closely with cross-functional teams comprising of data scientists, engineers, software developers, solution architects, and Logistics domain experts to offer comprehensive expertise in sustainment analytics services, as well as other sustainment support activities. The SME will engage in a diverse array of responsibilities, including growth, capability development, technical leadership for delivery, and driving thought leadership.

Note: Remote is acceptable with occasional requirements to travel to offices at U.S. locations.

At LMI, we’re reimagining the path from insight to outcome at The New Speed of Possible™. Combining a legacy of over 60 years of federal expertise with our innovation ecosystem, we minimize time to value and accelerate mission success. We energize the brightest minds with emerging technologies to inspire creative solutioning and push the boundaries of capability. LMI advances the pace of progress, enabling our customers to thrive while adapting to evolving mission needs. 

Lead Delivery of Solutions

• Empower clients to optimize the utilization of data generated by systems across the entire lifespan of assets. This data, accumulated over time by the enterprise, can be harnessed to boost system performance and mitigate operational risks effectively.
• Facilitate the adoption of data-driven techniques to include advanced analytics, AI/ML and modeling and simulation to enhance asset performance and reduce the total cost of ownership.
• Assist in the creation, rollout, and ongoing management of sustainment analytics solutions, designed to elevate the effectiveness of sustainment operations.
• Offer consultation services to clients seeking to improve their sustainment effectiveness through a range of approaches, including Asset Performance Management, Predictive and Prognostic Maintenance (PPMx), Predictive Logistics, Fleet Management, and Telematics.

Growth

• Collaborate with senior government leaders and key stakeholders to effectively communicate and champion the importance of advancing sustainment analytics and the advantages of adopting these analytic practices.
• Determine sustainment related emerging trends in AI/ML and assist markets in evaluating use cases and potential opportunities while offering solution development, capture, and proposal support.
• Prepare and coordinate working papers, briefings, and other documentation in support of sustainment modernization initiatives.

Solution Development

• Work with LMI’s innovation center to explore new technological advancements in sustainment to enhance our existing capabilities and create new ones, enabling us to stay relevant in the ever-evolving landscape of digitally enabled sustainment solutions.
• Facilitate the development of Concepts of Operation (CONOPS) for diverse clients, such as those involving sensor data collection (i.e. IoT), to provide critical insights that will guide government decisions regarding the most suitable implementation strategies.

Bachelor’s degree

Experience in the following areas:

• More than 7 years of practical experience as a technical expert, consultant, or specialist, actively involved

  in the delivery of data driven digital services and solutions related to sustainment activities.

• Demonstrated proficiency, extensive expertise, and practical hands-on experience in operations and sustainment, covering fleet management and sustainment support activities. This includes a strong background in technical management and leadership of technical teams, critical thinking, and a proven track record in the strategic planning and successful delivery of sustainment digital solutions.
• Experience with a diverse array of sustainment data sources, encompassing maintenance, reliability, fleet management and asset data. Expertise in maintenance and operations data, which includes a strong background in data collection, data cleansing, analytical development, and communicating outputs.
• Proven experience in the organization, planning, leadership, and management of technical teams, coupled with a track record of successfully collaborating with cross-functional teams.
• Strong interpersonal, verbal, presentation and writing skills to successfully deliver briefings and interact with executive client leadership.
• Ability to work independently and deliver high quality work under time constraints.
• Availability to travel

Preferred Qualifications

Master’s Degree

• Experience supporting commercial clients by applying best practices and leveraging cutting-edge technologies to deliver data-driven digital services and solutions tailored to sustainment activities.
• Understanding of deploying sustainment analytics at scale, including the development of strategies for extracting actionable insights from sustainment data through modeling techniques such as natural language processing, machine learning, and reliability analysis.
• Subject matter expertise in the following domains: maintenance and reliability, asset reliability and availability, asset lifecycle management, digital twins, predictive analytics, and asset performance management.
• Active or eligible for DOD Secret clearance

Targeted Salary Range: $120,000 - $185,000

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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