Junior Data Scientist - Clearance Required

Overview: 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.Responsibilities:Responsibilities:

• Demonstrate the ability to frame and scale data problems to analyze, visualize, and find data solutions.
• Innovative application of statistical and data science techniques in solutioning.
• Manipulate common data formats, including comma-delimited, text files, and JSON.
• Transform data and analysis into informative visualizations and interactive dashboards using open-source and commercially available tools.
• Derive insights and analytic narratives from data and visualizations for effective storytelling and clear communication in response to client research questions.
• Work in a fast-paced, solutions-oriented environment focused on client deliverables, analysis, and reporting.
• Possess ability to work in teams setting, including as a team lead, and independently

Qualifications:Qualifications:

• Bachelor's degree in science, data science, technology, engineering, mathematics, probability and statistics, biostatistics, computer science, economics, or other related business or technical discipline is required. Master's degree preferred.
• Active DoD Secret clearance required
• 1-3 years minimum experience in the field
• Experience working with tools, including object-oriented programming (Python, Java), computational analysis tools (R, MATLAB, SPARK-ML), and associated data science libraries (scikit-learn)
• Experience developing machine learning, data mining, statistical network, natural language processing, text analytics, and graph-based algorithms
• Experience in reliability/life analysis such as proportional hazard modeling (PHM), Reliability, Availability, and Maintainability (RAM) analysis, Reliability Centered Maintenance (RCM) processes and analysis.
• Experience with databases (SQL, S3, Redshift), data curation techniques (ETL, SPARK, Python), and connecting data to analytics and visualization products
• Experience creating meaningful data visualizations and interactive dashboards using platforms such as Tableau, Qlik, Power BI, RShiny, plotly, and d3.js to communicate findings and relate them back to how your insights create business impact
• Experience with algorithm, prototype, and application development and implementation in on-premise and cloud-based computing environments, such as Hadoop and AWS
• Superior communication skills, both oral and written

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