Data Scientist - Clearance Required

LMI; Pittsburgh (Allegheny County); On-site; USD 130,000 - 180,000; Full time

Job summary

LMI is seeking a Data Scientist to develop predictive and prescriptive analytics for Army AI Integration Center (AI2C). You will build models, run simulations, and translate complex outputs into actionable recommendations for sustainment, talent management, and recruiting domain decisions.

The role requires strong Python skills, experience with machine learning and operations research, and the ability to communicate results to both technical and non-technical stakeholders.

Qualifications

• Bachelor's degree in Data Science, Statistics, Mathematics, CS, OR, or related field or equivalent experience
• 3–5 years of data science or applied analytics experience with focus on predictive modeling and ML
• Proficiency in Python (pandas, numpy, scikit-learn, statsmodels) and/or R for data manipulation and model development
• Experience building and validating supervised and unsupervised ML models (regression, classification, clustering, time-series)
• Experience with data visualization tools to communicate findings effectively
• Experience with enterprise data platforms for data integration and pipeline development
• Familiarity with Git, Agile methodologies, and collaborative development practices
• Ability to communicate complex analytical concepts clearly to non-technical stakeholders
• Active Secret Clearance required

Responsibilities

• Design, develop, and deploy predictive and prescriptive models to support Army decision-making across multiple domains
• Develop and maintain analytical models and simulations to evaluate systems and processes
• Design and execute simulations (e.g., Monte Carlo) using Python libraries to assess behavior under uncertainty
• Apply OR techniques to address allocation and scheduling challenges
• Formulate and solve optimization problems using Python packages to evaluate alternatives
• Conduct quantitative trade studies and sensitivity analyses to inform decisions
• Develop statistical and probabilistic models to characterize system behavior and quantify risk
• Design computational experiments to assess model performance across scenarios
• Perform model verification, validation, and uncertainty quantification with empirical data
• Integrate and analyze structured and unstructured data to support modeling workflows
• Develop reusable Python-based analytics tools and workflows with good software practices
• Create analytical visualizations and dashboards to communicate outputs and uncertainties
• Implement monitoring and troubleshooting for reliability
• Document models and methodologies per Army/DoD standards
• Collaborate with UX/UI designers to integrate data science into user-facing apps
• Lead and mentor team members; engage with Army managers to validate requirements
• Travel: 10%

Skills

Python programming

ML modeling

Data visualization

Education

Bachelor's degree in Data Science or related field

Tools

Palantir Foundry

Git

Job description

Overview

LMI is seeking a skilled Data Scientist to join our team and contribute to developing innovative analytics capabilities in support of the Army's AI Integration Center (AI2C). This role focuses on building predictive models, surfacing data-driven insights, and translating complex analytical outputs into actionable recommendations that advance the Army's AI strategy. The ideal candidate brings strong foundations in predictive analytics and machine learning, with the ability to communicate findings clearly to both technical and non-technical stakeholders.

This position offers the opportunity to work at the intersection of data science and national defense—applying cutting-edge analytical methods to real-world Army challenges spanning talent management, equipment sustainment, recruiting, and training. Candidates should be self-directed, collaborative, and comfortable operating in a fast-paced, mission-driven environment.

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, develop, and deploy predictive and prescriptive models that support Army decision-making across sustainment, talent management, and recruiting domains
• Develop, implement, and maintain analytical models and simulations to evaluate complex systems, operational processes, mission effectiveness, and alternative courses of action.
• Design and execute discrete-event, agent-based, stochastic, and Monte Carlo simulations using Python libraries such as SimPy, Mesa, NumPy, and SciPy to assess system behavior, operational performance, and outcomes under uncertainty.
• Apply operations research techniques, including mathematical programming, optimization, stochastic modeling, queuing theory, and decision analysis, to address complex operational and resource allocation challenges.
• Formulate and solve linear, nonlinear, integer, and mixed-integer optimization problems using Python packages such as Pyomo, PuLP, SciPy.optimize, OR-Tools, and CVXPY to evaluate scheduling, logistics, resource allocation, and operational planning alternatives.
• Conduct quantitative trade studies, sensitivity analyses, scenario-based assessments, and what-if analyses to identify key performance drivers, evaluate operational alternatives, and inform decision-making.
• Develop statistical and probabilistic models using NumPy, SciPy, pandas, statsmodels, and PyMC to characterize system behavior, quantify uncertainty, and evaluate operational risks.
• Design and execute computational experiments, including design of experiments (DOE), parameter sweeps, Monte Carlo analysis, and sensitivity testing, to assess model performance and robustness across operational scenarios.
• Perform model verification, validation, calibration, and uncertainty quantification using empirical data, statistical testing, and subject matter expertise to establish confidence in analytical results.
• Integrate, transform, and analyze structured and unstructured data from multiple sources using pandas, NumPy, Polars, and associated Python data-processing libraries to support modeling, simulation, and optimization workflows.
• Develop reusable, modular, and reproducible Python-based analytical tools and computational workflows, leveraging software development best practices, version control, automated testing, and documented methodologies.
• Develop analytical visualizations, interactive dashboards, and decision-support tools using Matplotlib, Seaborn, Plotly, and Streamlit to communicate simulation outputs, optimization results, uncertainty, and operational tradeoffs.
• Implement monitoring, logging, and troubleshooting to ensure system reliability and availability
• Synthesize and communicate analytical findings, model assumptions, limitations, uncertainties, and actionable recommendations through technical documentation, reports, briefings, and presentations to technical and non-technical decision-makers.
• Build and maintain data pipelines and analytical workflows using Python, PySpark, and/or R, integrating with Army platforms such as Palantir Foundry and Army Vantage
• Collaborate closely with UX/UI designers and software developers to integrate data science capabilities into user-facing applications
• Knowledge of containerization tools (e.g. Docker, Docker-Compose, Kubernetes, etc.)
• Provide technical leadership and mentorship, growing team capabilities at the intersection of data science and mission-focused application development
• Engage with Army managers and subject matter experts to understand mission requirements, validate model assumptions, and build trust in analytical outputs
• Document models, methodologies, and analytic processes in accordance with Army and DoD standards

Percentage of Travel Required: 10%

Minimum Qualifications

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Operations Research, or a related quantitative field, or equivalent work experience
• 3–5 years of experience in data science or applied analytics, with demonstrated focus on predictive modeling and machine learning
• Proficiency in Python (pandas, numpy, scikit-learn, statsmodels) and/or R for data manipulation, statistical analysis, and model development
• Experience building and validating supervised and unsupervised ML models (regression, classification, clustering, time-series forecasting)
• Experience with data visualization tools and libraries (Plotly, D3.js, Recharts, Tableau, or similar) to communicate analytical findings effectively
• Experience with Palantir Foundry or comparable enterprise data platforms for data integration, pipeline development, and application support
• Familiarity with Git, Agile methodologies, and collaborative development practices
• Ability to communicate complex analytical concepts clearly to non-technical stakeholders and influence decisions through data
• Active Secret Clearance required

Additional Preferred Qualifications

• Knowledge of Natural Language Processing (NLP) techniques and applications
• Hands-on deployment experience across multiple environments and platforms
• Background working in strategic planning or consultant environments supporting government or DoD clients
• Proven track record of expanding technical scope or footprint with government customers
• Knowledge of the Army software development process and its technologies.
• 7+ years of directly related experience.
• Familiarity with human-centered design principles and integrating analytical outputs into user-facing applications
• Master’s degree in Computer Science, Software Engineering, Information Systems, or related field.

Target Salary Range

$130,000 - $180,000

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.

Job Locations

US-PA-Pittsburgh