LMI seeks an experienced Tactical Sports Scientist to serve on the integrated H2FMS technical and human performance team supporting CIMT.

H2FMS operates in Army GovCloud and integrates the vendor-provided H2F data capture application to produce readiness analytics for H2F practitioners and Army leaders.

The Tactical Sports Scientist provides advanced sports science, biomechanics, performance modeling, and wearable analytics expertise to ensure that H2FMS produces scientifically valid, operationally relevant insights for Soldier and unit readiness.

This role works closely with the Human Performance Specialist, Data Engineers, Cloud/DevSecOps personnel, and UI/UX designers to build domain-specific metrics, thresholds, algorithms, and analytic workflows.

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 civilian 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.

• Develop and validate analytic models for physical performance, load, fatigue, recovery, movement efficiency, and injury risk.
• Ensure analytic outputs derived from vendor-provided data reflect sports science best practices.
• Define calculation logic for readiness scores, performance flags, and biomechanical indicators.
• Interpret and validate data from wearables and monitoring technologies, including HR / HRV, GPS / positional data, Accelerometry, Sleep monitoring systems
• Advise the H2FMS technical team on reliability, sampling, sensor limitations, and data quality.
• Validate data fields, sampling structures, and data completeness flowing into H2FMS from the vendor application.
• Ensure sensor-derived and manual-entry data can be integrated into readiness models in Army GovCloud.
• Provide scientific specifications for ETL, transformation, and aggregation processes.
• Work with Data Engineers to implement algorithms, thresholds, normalization logic, and scoring models.
• Work with UI/UX designers to ensure scientific accuracy and interpretability of dashboards and visualizations.
• Participate in Agile ceremonies and provide scientific acceptance criteria for performance analytics.
• Ensure all analytic methods and outputs align with FM 7-22 and H2F doctrine.
• Apply current research in biomechanics, physiology, recovery science, and injury mitigation.
• Serve as a scientific reviewer for readiness features and analytic tools.
• Present analytic findings to CIMT leadership and H2FMS development teams.
• Contribute to documentation, SOPs, and training materials to help interpret model outputs.

Required

• Master’s degree in Sports Science, Biomechanics, Physiology, Kinesiology, or related field.
• 5+ years of experience applying performance science in tactical, military, or elite sports environments.
• Expertise analyzing and modeling wearable and sensor data.
• Experience developing performance, recovery, or injury risk models.
• Strong understanding of FM 7-22 and physical aspects of H2F.
• Ability to obtain a Secret clearance.
• Location: Remote, Travel up to 1-2 times per quarter to client HQ in Fort Eustis or LMI HQ in Tysons, Virginia. Additional travel to Army installations worldwide may be required 1-2 times per quarter.  

Desired

• PhD in a relevant performance science field.
• Certifications (CSCS, TSAC-F, PES, CES, USAW).
• Experience with H2F brigades, CIMT, TRADOC, or SOF human performance teams.
• Experience with performance dashboards, analytics platforms, or wearable APIs.
• Familiarity with Python/R or quantitative analysis methods.

Targeted Salary Range: $90,000-$155,000

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.

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