Logistics Management Institute

About Logistics Management Institute

Overview: This position is within the Advanced Analytics practice of LMI, a not-for-profit government consultancy, dedicated to the mission charter of agencies and organizations across government. Leverage your “science first” mentality, curiosity, technical expertise, and problem-solving skills to use computational experimentation with large-scale simulation models for determining optimal allocation and planning of resources within transportation networks. This includes enabling government to capitalize on the value proposition of advanced analytics, and the derivation of clear narratives that help our clients understand their data and how those insights address their research questions. **This position is located at a client site in Washington, DC** Responsibilities: Developing input data sets for large-scale inventory simulation analyses, from multiple data sources with diverse formats, and performing quality assurance on that data. Leveraging design of experiments thinking to develop appropriate parameter sweep scenarios to best generate optimal and prescriptive decision making insights. Interpreting simulation output to clearly identify findings, caveats, assumptions, and implications. Transforming simulation data and analysis outputs into clear data visualizations and/or reports to communicate findings. Deriving analytic narratives from experiment insights for effective storytelling and clear communication in response to specific research questions. Ability to work in a fast-paced, solutions-oriented environment. Possess the ability to work in teams and independently. Qualifications: Bachelor’s degree or higher in operations research, data science, mathematics, statistics, economics, physics, computer science, engineering, or other quantitative discipline. 2-5 years of overall experience. Expertise in modeling and simulation theory and methods (e.g., discrete-event simulation) and considerations specific to stochastic modeling, for example, best practices related to random number generators, random seed, steady state, and replications. Experience with programming (e.g., Python, Java, R). Experience with commercial simulation modeling platforms, with strongly preferred experience with JDA and TMOD for modeling transportation networks and route optimization. Experience working with large and diverse data sets and database technologies. Working knowledge of SQL is preferred. Superior communication skills, both oral and written. #LI-SH1

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Company Type: Private

Company Size: 1001 - 5000

Revenue: 100 - 500 million (USD)

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Job Ads found: 2482

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Hiring Locations: 51

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