LMI: Innovation at the Pace of Need™
At LMI, we’re reimagining the path from insight to outcome at the new speed of possible. Combining a legacy of over 60 years of federal expertise with our innovation ecosystem, we minimize time to value and accelerate mission success. We energize the brightest minds with emerging technologies to inspire creative solutioning and push the boundaries of capability. LMI advances the pace of progress, enabling our customers to thrive while adapting to evolving mission needs.
This position is embedded within our Advanced Analytics & AI practice. Leverage your curiosity and problem-solving skills to explore, discover, and predict patterns contained within data sets for a wide range of government clients. This includes the derivation of clear narratives that help our clients understand their data and how those insights address their research questions.
This data scientist will work as part of a team of experienced data scientists, data engineers, and data analysts to support advanced analytics projects for the Chief Digital and Artificial Intelligence Office (CDAO) of the Department of Defense. Responsibilities include:
- Frame and scale data problems to analyze, visualize, and find data solutions.
- Manipulate common data formats, including comma-delimited, text files, and JSON.
- Build robust, scalable data pipelines using big data technologies such as Spark to enable predictive and prescriptive modeling.
- Develop and deploy modeling capabilities (e.g., simulation, machine learning, statistical forecasting).
- Work with the technical lead on solutioning, timelines, and feasibility.
- Work in a fast-paced, solutions-oriented environment focused on client deliverables, analysis, and reporting.
- Active DoD Secret clearance
- Bachelor’s degree in data science, mathematics, statistics, economics, computer science, engineering, or a related business or quantitative discipline
- Experience working with tools, including object-oriented programming (Python, Java), computational analysis tools (R, MATLAB), big data frameworks (Spark or PySpark), and associated data science libraries (scikit-learn)
- Data science methods related to data architecture, data munging, data and feature engineering, and predictive analytics
- Experience developing and deploying modeling tools and capabilities
- Working knowledge of databases and SQL; preferred qualifications include linking analytic and data visualization products to database connections
- At least 10–15 years of experience in the field
- Superior communication skills, both oral and written
- DoD experience preferred
- Unstructured text and natural language processing
- Experience with Databricks, Qlik, and the Advana analytics platform
- Previous experience working with supply chain or maintenance data or processes
- Supervising algorithm implementation in on-premise and cloud-based computing environments
- Developing and implementing statistical, machine learning, and heuristic techniques to create descriptive, predictive, and prescriptive analytics as well as to develop statistical tests to make data-driven recommendations and decisions