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Posted by: LMI on Oct 11, 2021


Tysons , VA

Job Description:

LMI is a consultancy dedicated to powering a future-ready, high-performing government, drawing from expertise in digital and analytic solutions, logistics, and management advisory services. We deliver integrated capabilities that incorporate emerging technologies and are tailored to customers' unique mission needs, backed by objective research and data analysis. Founded in 1961 to help the Department of Defense resolve complex logistics management challenges, LMI continues to enable growth and transformation, enhance operational readiness and resiliency, and ensure mission success for federal civilian and defense agencies.

LMI is currently seeking an Operations Research Analyst (ORSA) to join our growing Operations Research Systems Analyst team in Tysons, VA. In this role, you will analyze data for actionable insight and develop custom software solutions to address client problems.

The Operations Research Analyst will: Perform data analysis using in-house databases, modeling, simulation, and other analytical tools Participate in ongoing research to identify, develop, evaluate, and apply new concepts in inventory or supply chain risk management Develop, test, and document software to model complex systems Work as part of a multi-disciplinary team in a solutions-oriented environment focused on client deliverables and analysis Communicate with clients through written reports and oral presentations Interpreting and developing data visualizations of simulation output to clearly convey findings Framing and scaling problems to effectively analyze, visualize and find solutions to complex decision problems Deriving insights and analytic narratives from data and visualizations for effective storytelling and clear communication in response to specific research questions Possess the ability to work with and manipulate common data formats, including comma-delimited, text files, and JSON Transforming data and analysis into informative data visualizations and/or interactive dashboards using open source and commercially available visualization and dashboard tools

Minimum Qualifications: Bachelor's degree or higher in operations research, data science, mathematics, statistics, economics, physics, computer science, engineering, or other quantitative discipline required. Master's degree or higher preferred. Experience with C++ and Python 3-5+ years of related experience is preferred Experience performing analyses with stochastic simulation models. Experience using optimization solvers on linear and mixed-integer programs (open source or commercial). Experience working with tools including object-oriented programming (Python, C++, Java, etc), computational analysis tools (R, MATLAB), and associated data science libraries (scikit-learn). Working knowledge of databases and SQL is desired. Preferred qualifications include linking analytic and data visualization products to database connections. Familiarity with analytical and simulation modeling-course work may qualify. Keen attention to detail and solid analytical skills Eligibility for a Security Clearance (US citizenship) is required.Preferred Qualifications: Master's degree in mathematics, statistics, physics, computer science, engineering, data science or a related business or quantitative discipline. Experience developing algorithms, writing modeling software, and analyzing complex systems Familiarity with large scale, multi-echelon, military inventory systems #LI-SH1

EEO Statement
LMI is an Equal Opportunity Employer-all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.

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About LMI

LMI is a consultancy dedicated to improving the business of government, drawing from deep expertise in advanced analytics, digital services, logistics, and management advisory services. Established as a private, not-for-profit organization in 1961, LMI is a trusted third party to federal civilian and defense agencies, free of commercial and political bias.

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