AI/ML Engineer - Clearance Required

LMI seeks an experienced AI/ML Engineer (Data Scientist) to support the U.S. Army’s Holistic Health & Fitness (H2F) initiative as part of the Analytics team within the H2F Program Support Team. The role involves developing and operationalizing analytic models to support readiness, injury-risk analysis, and user engagement insights within the H2FMS.

Location: Remote (US)

Salary: $110,986–$195,154/yr

Responsibilities

• Develop and implement statistical and machine learning models supporting readiness assessment, performance analysis, and injury-risk awareness.
• Apply appropriate analytic methods based on data characteristics, scientific guidance, and Government priorities.
• Ensure analytic approaches are transparent, interpretable, and suitable for operational decision support.
• Support validation, testing, and refinement of analytic models under Government and senior scientific direction.
• Assess model performance, limitations, assumptions, and potential bias.
• Collaborate with epidemiologists and research psychologists to ensure analytic outputs align with scientific intent.
• Work with data engineers to support feature development, data preparation, and analytic dataset construction.
• Assist in identifying data quality issues that may impact model performance.
• Ensure analytic inputs align with approved data definitions and governance standards.
• Collaborate with software teams to support integration of analytic outputs into dashboards, reports, and user-facing decision-support tools.
• Support development of repeatable analytic workflows and documentation.
• Assist in troubleshooting analytic issues in coordination with data and software teams.
• Contribute to documentation of analytic methods, assumptions, limitations, and results.
• Support preparation of analytic summaries, briefings, and materials for Government stakeholders.
• Clearly communicate analytic findings in a manner appropriate for non-technical audiences.

Requirements

• Bachelor’s degree in Data Science, Statistics, Computer Science, Applied Mathematics, or a related field.
• Demonstrated experience applying statistical analysis or machine learning techniques to real-world data problems.
• Familiarity with data preparation, feature engineering, and model evaluation concepts.
• Experience working with structured and semi-structured data.
• Ability to collaborate effectively within multidisciplinary teams spanning analytics, research, and software development.
• Strong analytical reasoning and communication skills.
• Ability to obtain and maintain a Secret security clearance.