Epidemiologist; MSKI - Clearance Required

Overview

LMI seeks an experienced Epidemiologist with a focus on Musculoskeletal Injury (MSKI) to support the U.S. Army’s Holistic Health & Fitness (H2F) initiative as a member of the Analytics functional team within the H2F Program Support Team.
This position requires a
Secret security clearance. This position is an on-site position in Newport News, VA.

The Epidemiologist is responsible for applying population-level epidemiological methods to analyze injury incidence, prevalence, risk factors, and outcomes related to MSKI across Army populations. This role supports readiness assessment, injury‑risk awareness, and evidence‑based decision support within the Holistic Health and Fitness Management System (H2

FMS). The role is analytic and advisory in nature and does not provide clinical care or treatment recommendations.

The Epidemiologist works closely with the Technical Project Manager, data engineers, data governance specialists, AI/ML engineers, research psychologists, tactical sports scientists, and software teams to ensure MSKI‑related data are appropriately structured, analyzed, and integrated into analytics, dashboards, and decision‑support products delivered through the Government‑managed H2F application.

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.

• Conduct population‑level analyses of musculoskeletal injury incidence, prevalence, severity, and outcomes across Army populations.
• Identify injury patterns, trends, and risk factors related to training exposure, workload, recovery, and readiness.
• Support development and refinement of injury surveillance approaches aligned with Army H2F objectives.
• Apply epidemiological and biostatistical methods to assess relationships between MSKI and contributing factors such as workload, conditioning, sleep, nutrition, and behavioral indicators.
• Collaborate with tactical sports scientists and research psychologists to contextualize injury findings within performance and readiness frameworks.
• Support development of evidence‑based indicators and analytic constructs related to MSKI risk.
• Work with data engineers and data scientists to ensure MSKI‑related data are appropriately structured, governed, and integrated within H2
  
  FMS.
• Support translation of epidemiological findings into analytic features, metrics, and model inputs.
• Assist in validation and interpretation of analytic models incorporating injury and health data.
• Support preparation of analytic products, briefings, and summaries that communicate MSKI trends and insights to Government stakeholders.
• Clearly articulate assumptions, limitations, and appropriate use of epidemiological findings.
• Contribute to evidence‑based recommendations that inform injury‑risk awareness and readiness discussions (without providing clinical guidance).
• Contribute to documentation of analytic methods, data sources, assumptions, and limitations.
• Support adherence to Government data governance, privacy, and usage requirements.
• Coordinate with other analytics and research team members to ensure analytic consistency across H2
  
  FMS products.

Required Qualifications

• Master’s degree or PhD in Epidemiology, Public Health, Biostatistics, or a closely related field.
• Demonstrated experience conducting epidemiological analyses, preferably related to musculoskeletal injury, injury prevention, or occupational health.
• Strong understanding of population‑level health data, surveillance methods, and statistical analysis.
• Experience…