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LMI

Data Scientist

LMI

. Support development, testing, and refinement of forecasting and analytics models for ammunition consumption and resupply .

Posted 10/2/2026full-timeRemote • United StatesJuniorMid-Level💰 $130,000 - $160,000 per yearWebsite

Core Competencies

Role fit
Core Competencies

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Proficient in developing and refining forecasting and analytics models using Python and SQL, with a strong focus on data preparation and analysis. Capable of translating complex analytical findings into actionable insights for non-technical stakeholders while supporting Agile project management.

Highest-signal resume keywords
Python ProgrammingSQL Data AnalysisRegression Model DevelopmentData Visualization ToolsAgile Methodologies

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Data SciencePredictive AnalyticsStatistical AnalysisModel ValidationData PreparationDescriptive AnalyticsDiagnostic AnalyticsTime Series AnalysisClassification ModelsQuantitative Analysis
Soft Skills
Critical ThinkingCommunication SkillsDetail-OrientedSelf-DirectedProblem-Solving
Tools & Technologies
VantagePower BITableauGitJIRAConfluence
Certifications & Qualifications
Active SECRET Clearance
Industry Keywords
Ammunition ManagementSupply Chain AnalyticsLogistics ProcessesData WarehousingEnterprise Data Analytics

Tech Stack

Tools & technologies
NumpyPandasPythonScikit-LearnSQLTableau

About the role

Key responsibilities & impact
  • Support development, testing, and refinement of forecasting and analytics models for ammunition consumption and resupply
  • Maintain and enhance Vantage-based analytics, dashboards, and data products, including incorporating new data sources
  • Assist in integrating and validating data into Vantage pipelines to centralize munitions data
  • Conduct descriptive, diagnostic, and predictive analytics on historical ammunition consumption and unit forecast data
  • Identify trends, anomalies, and opportunities for improvement
  • Support requirement-gathering sessions with logisticians, ammunition SMEs, and Government stakeholders
  • Define analytical use cases, data needs, and model enhancements
  • Develop and maintain reproducible analytical workflows using Python, SQL, and related tools
  • Document model logic, assumptions, and limitations
  • Assist in monitoring model performance and key metrics
  • Prepare visualizations and summary analyses for leadership decision-making, including monthly status reports and briefings
  • Support project backlog management by creating and updating user stories and technical tasks related to data science work

Requirements

What you’ll need
  • Bachelor’s degree in data science, statistics, mathematics, computer science, engineering, business analytics, or related discipline
  • 2–5 years of experience in data science, analytics, or a closely related field
  • Demonstrated experience with Python (e.g., pandas, scikit-learn, numpy) and SQL for data preparation, analysis, and basic modeling
  • Experience building and validating regression, time series, or classification models
  • Experience working with large, structured datasets in relational databases or data warehouses
  • Strong quantitative and critical thinking skills; ability to translate ambiguous business questions into analytical problems and solutions
  • Ability to communicate analytical findings to non-technical stakeholders in clear, concise terms
  • Self-directed, detail-oriented, and comfortable working in an Agile environment with shifting priorities
  • Active or attainable SECRET clearance; only US Citizens can obtain a clearance
  • Experience supporting an enterprise data analytics platform (e.g., Army Vantage, Army Data Platform, or similar) preferred
  • Familiarity with Army logistics processes, ammunition management, or supply chain analytics preferred
  • Experience with dashboarding/BI tools (e.g., Power BI, Tableau, or Vantage-native visualization tools) preferred
  • Experience with version control (e.g., Git) and Agile/Scrum practices (e.g., JIRA, Confluence) preferred
  • Exposure to ML model monitoring and MLOps concepts preferred