Principal Analytics Engineer

Overview

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.

LMI is seeking a Principal Systems Engineer who can blend expertise in physics‑based modeling with a strong grasp of networked data systems—both in the space domain and across terrestrial and cyber environments. You will be LMI’s primary technical interface to an SES-level customer and you will drive the design, simulation, and evaluation of end‑to‑end data‑flow architectures that span satellite constellations, ground‑segment infrastructures, and secure cyber‑networks, providing actionable insight for force‑design, resiliency, survivability, and strategic superiority.

This position is perfect for an analytical thinker who thrives on applying rigorous theory to real‑world space challenges, using data‑driven simulations to guide high‑stakes decisions in defense and national security space sectors. This is an on‑site role in Colorado Springs, CO.

• Serve as primary technical advisor to our SES customer and interface with other senior government stakeholders and FFRDC, SETA, and developer contractors.
• Communicate complex subjects across a wide range of audiences.
• Lead technical team building physics‑based and network‑centric models that capture orbital dynamics, RF propagation, and data‑link performance for space‑data, ground‑data, and cyber networks.
• Oversee the performance of high‑fidelity scenario analysis by running Monte‑Carlo, sensitivity, and uncertainty‑quantification studies to assess performance under nominal, contested, and degraded‑environment conditions (e.g., debris fields, cyber‑attacks, spectrum congestion).
• Create vulnerability and trade‑study frameworks by developing analytical recommendations that quantify network survivability, cyber‑risk exposure, and data‑integrity across the full data path—from sensors in orbit to ground‑station processing and downstream enterprise networks.
• Translate simulation outputs into clear recommendations for architecture upgrades, resource allocation, and capability‑gap mitigation, feeding directly into force‑design and acquisition roadmaps.
• Partner with software engineers, data scientists, cyber‑security specialists, and mission planners to embed models into larger analytical pipelines and automated decision‑support systems.
• Process data to extract insights—produce visualizations that illustrate network health, latency heat‑maps, threat outcomes, etc.
• Assist in authoring technical reports, briefing decks, and strategic whitepapers; present findings to senior leadership and external stakeholders; contribute to conference submissions where appropriate.
• Guide junior systems and analytic engineers in best practices for integrated space‑cyber‑ground modeling and foster a culture of interdisciplinary learning.

• B.S. in Physics, Applied Physics, Aerospace Engineering, Operations Research, or a related field with a strong emphasis on theoretical modeling.
• At least 8+ years of experience in space‑related modeling, simulation, and analysis (industry, national lab, government, or advanced research settings).
• Strong expertise in physics and/or theory relevant to space: orbital mechanics, astrodynamics, electromagnetics, radiation effects, satellite communications (ground and space‑based), position, navigation, and timing (PNT) systems, and systems engineering principles.
• Demonstrated ability to abstract theoretical concepts into practical models, simulations, and analytical frameworks…