Role Overview
The ideal candidate will join LMI’s team to contribute to developing innovative analytics capabilities in support of the Army’s AI Integration Center (AI2C). The role focuses on building predictive models, surfacing data-driven insights, and translating complex analytical outputs into actionable recommendations.
What You Will Do
Responsibilities include designing, developing, and deploying predictive and prescriptive models, developing analytical models and simulations, and applying operations research techniques to address complex operational and resource allocation challenges.
Why It Might Be a Fit
The ideal candidate will be self-directed, collaborative, and comfortable operating in a fast-paced, mission-driven environment, with strong foundations in predictive analytics and machine learning, and the ability to communicate findings clearly to both technical and non-technical stakeholders.
Requirements
- 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
To apply for this job please visit careers-lmi.icims.com.

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