Data Scientist - Clearance Required

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    "datePosted": "2026-05-21T04:00:00.000Z",
    "description": "<h2>Overview</h2>\n<p>LMI is seeking a Data Scientist to support advanced analytical efforts focused on future space architectures, including sustained space maneuver and resilient orbital operations. In this role, you will develop and apply quantitative methods, statistical models, and data-driven techniques to analyze outputs from modeling, simulation, and trade studies.</p>\n<p>You will work closely with analysts, software developers, and systems engineers to transform large volumes of simulation and scenario data into insightful, decision-relevant results that inform force design and capability development.</p>\n<p>This position is ideal for a data scientist who thrives in analytically complex, low-data, high-uncertainty environments, and who is comfortable working with both structured and exploratory analytical problems.</p>\n<p> </p>\n<p>This is an on-site role in Colorado Springs, CO.</p>\n<p> </p>\n<p>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.</p>\n<p> </p>\n<p>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.</p>\n<h2>Responsibilities</h2>\n<p><strong>Responsibilities</strong></p>\n<ul>\n <li>Develop and apply statistical, mathematical, and computational methods to analyze modeling and simulation outputs </li>\n <li>Support execution of trade studies and design-of-experiments approaches, including parameter sweeps and sensitivity analysis </li>\n <li>Process and analyze large-scale simulation datasets, identifying key drivers, trends, and relationships </li>\n <li>Develop models to support uncertainty quantification, risk analysis, and performance assessment </li>\n <li>Collaborate with trade space analysts to ensure analytical methods align with study objectives and decision needs </li>\n <li>Work with backend developers to integrate analytical workflows into RAPTR® and related platforms </li>\n <li>Develop data pipelines and scripts to support repeatable and scalable analysis </li>\n <li>Visualize analytical results and communicate findings to both technical and non-technical stakeholders </li>\n <li>Contribute to technical reports, briefings, and recommendations supporting force design and architecture evaluation </li>\n <li>Explore advanced analytical techniques (e.g., surrogate modeling, optimization methods, or machine learning) where appropriate </li>\n</ul>\n<h2>Qualifications</h2>\n<p><strong>Required Qualifications</strong></p>\n<ul>\n <li>Bachelor’s degree in Data Science, Operations Research, Applied Mathematics, Physics, Computer Science, or a related quantitative field </li>\n <li>5+ years of experience in data science, quantitative analysis, or modeling & simulation environments </li>\n <li>Strong proficiency in Python (preferred) or similar analytical programming languages </li>\n <li>Experience with statistical analysis, including regression, hypothesis testing, and multivariate analysis </li>\n <li>Experience working with simulation or experimental data </li>\n <li>Familiarity with data analysis libraries such as NumPy, Pandas, and SciPy </li>\n <li>Experience designing and executing data-driven analytical workflows </li>\n <li>Ability to operate in loosely defined problem spaces and adapt analytical approaches as needed </li>\n <li>Strong problem-solving and critical thinking skills </li>\n <li>Excellent communication and collaboration skills </li>\n</ul>\n<p><strong>Preferred Qualifications</strong></p>\n<ul>\n <li>Experience supporting modeling & simulation, wargaming, or defense-related analytical efforts </li>\n <li>Familiarity with design of experiments (DOE), optimization techniques, or Monte Carlo methods </li>\n <li>Experience developing surrogate models or reduced-order models for complex simulations </li>\n <li>Exposure to space domain problems (e.g., orbital systems, satellite operations, mission analysis) </li>\n <li>Experience with data visualization tools such as Matplotlib, Plotly, or similar </li>\n <li>Familiarity with cloud-based or distributed computing environments </li>\n <li>Advanced degree (M.S. or Ph.D.) in a relevant quantitative field </li>\n <li>Active TS/SCI clearance </li>\n</ul>\n<p><strong>Security Clearance Requirements</strong></p>\n<p>Candidate must be eligible to obtain a TS/SCI clearance and willingness to obtain a CI Poly. Candidates with an active TS/SCI or TS with SCI eligibility will be given preference.</p>\n<p> </p>\n<p>Target salary range: $111,426 - $192,890</p>\n<p> </p>\n<p>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.</p>\n<p> </p>\n<p>#LI-SH1</p>",
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