Data Scientist - Clearance Required

Overview

LMI is seeking a Data Scientist to support a Special Operations Command (SOCOM) mission partner with advanced analytics, predictive modeling, natural language processing, and artificial intelligence and machine learning (AI/ML) product development.

The Data Scientist will analyze complex historical and operational datasets, convert data into machine-learning-ready formats, identify trends and predictive features, develop and validate statistical and machine learning models, and provide decision-quality insights that support resource forecasting, operational planning, and modernization. This position will work as part of a cross-functional data science product team to develop, integrate, govern, sustain, and document mission-relevant applications, dashboards, models, and research products.

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 achieve mission success.

This position is on-site at Fort Bragg and requires an active Secret security clearance with the ability to obtain a Top Secret clearance.

• Analyze historical operational records, program execution data, and related datasets to identify trends, relationships, anomalies, and key features for predictive modeling.
• Clean, normalize, reconcile, label, and transform structured and unstructured data from multiple sources into traceable, machine-learning-ready datasets.
• Develop, test, and refine predictive models to forecast resource consumption and annual rate projections with a maximum error margin of 1%.
• Apply statistical analysis, feature engineering, time-series forecasting, regression, ensemble methods, and other appropriate techniques to improve model accuracy, reliability, explainability, and operational usefulness.
• Establish model validation, back-testing, sensitivity analysis, error analysis, and performance-monitoring methods; document assumptions, limitations, risks, and sources of uncertainty.
• Develop natural language processing and generative AI solutions, including large language models tailored to approved business, operational, and intelligence use cases.
• Develop projects that automate or augment human cognitive workload and respond rapidly to emerging operational data and data science requirements.
• Collaborate with AI/ML engineers, data engineers, software developers, cybersecurity personnel, and mission stakeholders to integrate validated models and analytical outputs into secure web-based applications and enterprise workflows.
• Support enterprise synchronization, integration, governance, security, sustainment, and adoption of data science and AI/ML products across multiple mission teams and stakeholder organizations.
• Translate complex analytical findings into clear, actionable insights and recommendations for technical teams, program managers, operational users, and senior mission-partner leaders.
• Develop and maintain customer-focused data science products, including applications, dashboards, analytical models, and research projects, through their full product life cycle.
• Produce analytical reports, dashboards, briefings, and decision-support products that communicate trends, insights, model performance metrics, and recommendations.
• Maintain comprehensive documentation of data sources, methodologies, feature definitions, model logic, validation results, system dependencies, workflows, and repeatable analytical processes.
• Develop user guides, training materials, demonstrations, and knowledge-transfer products sufficient for a qualified practitioner to assume future operation and sustainment of the application or capability.
• Provide rapid-response analytical and…