Job description

The Data Scientist – SME will serve as the lead technical expert for optimization and advanced analytics within the portfolio. This role will own the design and implementation of prescriptive analytics solutions—especially optimization models—that set safety stock levels, recommend resupply quantities, and balance risk and cost across the supply chain. The SME will work closely with logisticians, ammunition SMEs, and data engineers to operationalize prescriptive decision support tools in Army Vantage and related environments. 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. Responsibilities • Continue to improve processes that: • Recommend ideal resupply quantities by installation and ammunition type • Align regional inventory to demand, reduce excess shipments and storage waste, and safeguard against stock-outs • Advance the Army along the analytics continuum from descriptive/diagnostic to predictive/prescriptive analytics, ensuring models are operationally actionable. • Work closely with logistician and ammunition SMEs to formulate, implement, and tune linear, mixed-integer, stochastic, and multi-objective optimization models that consider: • Forecasted demand (unit forecasts and ML-based forecasts) and available depot stock • Transportation costs, storage constraints, and depot capacity. • Additional optimization constraints, decision variables, and objectives that reflect real-world policies, doctrine, and operational constraints: • Readiness priorities and surge requirements. • Collaborate with data engineers to ensure pipelines provide clean, timely input data and to embed optimization models into the application and Vantage workflows. • Design and implement model performance metrics and KPIs and conduct near real-time monitoring of model impact. • Lead experimentation, scenario analysis, and sensitivity studies. • Provide technical leadership and mentorship to journeyman data scientists, guiding best practices in modeling and optimization. • Support briefings to senior Army leadership and stakeholders, clearly explaining model design, trade-offs, and operational impact. Minimum Qualifications • Bachelor's degree in operations research, industrial engineering, applied mathematics, statistics, computer science, or related quantitative field; masters or PhD. • 7+ years of experience in advanced analytics, operations research, or data science, with direct responsibility for optimization model design and deployment. • Demonstrated expertise in: • Linear and mixed-integer optimization, stochastic optimization, and/or robust optimization. • Modeling tools and libraries (e.g., Pyomo, Gurobi, CPLEX, OR-Tools, or similar). • Integrating optimization models with predictive models (e.g., ML-driven demand forecasts). • Proven experience translating complex mission and business objectives into formal optimization formulations and delivering production-caliber solutions. • Experience working with cross-functional teams (data engineers, logisticians, software developers, and mission owners) in an Agile environment. • Excellent written and oral communication skills, including experience briefing senior leaders and explaining trade-offs to non-technical audiences. • Active SECRET clearance ; U.S. citizenship required. Desired Qualifications • Experience in DoD logistics, supply chain, or munitions management; familiarity with Army ammunition systems and processes. • Prior work with enterprise data platforms (e.g., Army Vantage, Army Data Platform) and AWS GovCloud or similar secure cloud environments. • Familiarity with model lifecycle management, including validation, verification, and continuous improvement processes in operational environments. • PMP and/or SAFe/Agile certifications Target salary range: $145,000-$180,000 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. US-Remote We can recommend jobs specifically for you! Click here to get started.

Requirements

Must-haves

Recommend ideal resupply quantities by installation and ammunition type
Align regional inventory to demand, reduce excess shipments and storage waste, and safeguard against stock-outs
Advance the Army along the analytics continuum from descriptive/diagnostic to predictive/prescriptive analytics, ensuring models are operationally actionable.
Work closely with logistician and ammunition SMEs to formulate, implement, and tune linear, mixed-integer, stochastic, and multi-objective optimization models that consider:
Forecasted demand (unit forecasts and ML-based forecasts) and available depot stock
Transportation costs, storage constraints, and depot capacity.
Additional optimization constraints, decision variables, and objectives that reflect real-world policies, doctrine, and operational constraints:
Readiness priorities and surge requirements.
Collaborate with data engineers to ensure pipelines provide clean, timely input data and to embed optimization models into the application and Vantage workflows.
Design and implement model performance metrics and KPIs and conduct near real-time monitoring of model impact.
Lead experimentation, scenario analysis, and sensitivity studies.
Provide technical leadership and mentorship to journeyman data scientists, guiding best practices in modeling and optimization.
Support briefings to senior Army leadership and stakeholders, clearly explaining model design, trade-offs, and operational impact.
Bachelor's degree in operations research, industrial engineering, applied mathematics, statistics, computer science, or related quantitative field; masters or PhD.
7+ years of experience in advanced analytics, operations research, or data science, with direct responsibility for optimization model design and deployment.
Linear and mixed-integer optimization, stochastic optimization, and/or robust optimization.
Modeling tools and libraries (e.g., Pyomo, Gurobi, CPLEX, OR-Tools, or similar).
Integrating optimization models with predictive models (e.g., ML-driven demand forecasts).

Nice-to-haves

Experience in DoD logistics, supply chain, or munitions management; familiarity with Army ammunition systems and processes.
Prior work with enterprise data platforms (e.g., Army Vantage, Army Data Platform) and AWS GovCloud or similar secure cloud environments.
Familiarity with model lifecycle management, including validation, verification, and continuous improvement processes in operational environments.
PMP and/or SAFe/Agile certifications
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Keywords to mirror

aimlagileaws

Platform: icims
Effort: medium