OverviewLMI is seeking a Mid-Level Analytics Engineer with deep expertise in physics and theoretical modeling to join our dynamic team focused on the space domain. In this role, you will leverage advanced physics principles to develop, simulate, and analyze complex space infrastructure systems including satellite constellations, ground stations, orbital networks, and resilient architectures. Your work will directly inform analytical recommendations for future force design decisions and optimizing space capabilities for mission effectiveness, survivability, resiliency, 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.
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.
Responsibilities- Design and implement physics-based models for space infrastructure, incorporating orbital dynamics, electromagnetic propagation, sensor phenomenology, environmental effects, and multi-domain interactions.
- Conduct high-fidelity simulations and analyses of space systems, evaluating performance under various scenarios (e.g., nominal operations, contested environments, debris fields).
- Develop analytical frameworks to assess system vulnerabilities, trade-offs, and optimization opportunities, using tools like Monte Carlo methods, sensitivity analysis, and uncertainty quantification.
- Translate simulation results into actionable recommendations for force design, including architecture enhancements, resource allocation, and capability gaps.
- Collaborate with software engineers, data scientists, and decision-makers to integrate models into broader analytical pipelines and decision-support systems.
- Build and maintain scalable simulation environments, ensuring models are computationally efficient and validated against empirical data.
- Perform data analysis on large datasets from simulations, telemetry, or open-source intelligence to derive insights and visualize outcomes.
- Contribute to technical reports, briefings, and strategic recommendations for stakeholders, including potential publication or presentation at industry conferences.
- Mentor junior team members and help shape best practices in space-domain physics modeling.
QualificationsRequired:- B.S. in Physics, Applied Physics, Aerospace Engineering, Operations Research, or a related field with a strong emphasis on theoretical modeling.
- At least 4+ years of experience in space-related modeling, simulation, and analysis (industry, national lab, government, or advanced research settings).
- Strong expertise in physics and 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 that drive decision-making.
- Experience with simulation tools such as STK (Systems Tool Kit), GMAT, FreeFlyer, AFSIM, or custom-built propagators.
- Familiarity with force design concepts, mission analysis, or wargaming in space or multi-domain operations.
- Strong problem-solving skills and the ability work independently with limited, if any, technical definition of analytical problems.
- Excellent communication and teamwork abilities.
Desired: - Advanced degree (M.S. or Ph.D.) in Physics, Applied Physics, Aerospace Engineering, Operations Research, or a related field with a strong emphasis on theoretical modeling.
- Background in space domain infrastructure analysis, including constellation design, coverage modeling, or resilience assessments.
- Experience with advanced techniques like physics-informed machine learning, agent-based modeling, or game theory for strategic recommendations.
- Knowledge of high-performance computing (HPC), parallel processing, or cloud-based simulation environments (e.g., AWS, Azure).
Security Clearance Requirements:Candidate must possess an active TS/SCI or TS with SCI eligibility clearance and a willingness to obtain a CI Poly.
Target salary range: $92,100 - $160,000
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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LMI is an Equal Opportunity Employer. LMI is committed to the fair treatment of all and to our policy of providing applicants and employees with equal employment opportunities. LMI recruits, hires, trains, and promotes people without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, pregnancy, disability, age, protected veteran status, citizenship status, genetic information, or any other characteristic protected by applicable federal, state, or local law. If you are a person with a disability needing assistance with the application process, please contact
Colorado Residents: In any materials you submit, you may redact or remove age-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.
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