Graduate Fellow Program 2024 (Advanced Analytics & AI)

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 broad-based program will provide the opportunity for new graduates with Master's degrees to develop analytic and consulting skills in support of the government. Participants will participate in project management and program development within the broad spectrum of public policy management and be exposed to a diverse mix of economics, finance, business and information technology, mathematics, statistics, operations research, and procurement. Graduate Fellows will start work in July, 2024.

This position is in our Advanced Analytics & AI Group. This position may be located in Tysons, VA or at a client location in the Washington, DC area.

Work primarily on short-term and mid-term tasks with technical supervision from project leaders and/or senior level consulting staff.
• Assist in evaluating results of studies, drafting reports and preparing analyses for review.
  Perform research, using models to analyze relevant project issues and management processes.
• Develop and/or use databases and spreadsheets; assist with data collection, data analysis, and library research.
• Perform data quality and data assurance reviews; conduct data analyses using qualitative and quantitative methods, prepare summary displays to report analysis results and findings.
• Contribute to team's preparation of project briefings, study findings, reports, conclusions and recommendations.
• As the program director finds appropriate, lead project sub-tasks, including managing the consulting staff and working directly with the client.
• Provide technical assistance to proposal managers and/or senior staff on preparation of proposal for new and follow-on work.
• Contribute to, and participate in, group meetings with clients.
• Respond to internal and external substantive questions and inquiries on assigned tasks and projects.
• Give clear oral and written explanations of assigned tasks, relevant issues, analytic approach, and results.
• Present project methodologies and findings to LMI staff and clients.
• The Graduate Fellow will also work with Forge, LMI's internal technology accelerator and innovation hub, to develop technology solutions for LMI and its federal government clients.
• Apply machine learning and data science approaches to initiate, develop, and deliver AI within web-based applications.
• Work within a team of data scientists, computer scientists, application developers, product managers, and designers to integrate AI/ML into applications to automate and improve business processes, data quality, and user experience.
• Identify opportunities where AI/ML or modeling and simulation can generate business insights or improve business processes
• Develop and implement digital and analytic approaches
• Work with product designers, application developers, infrastructure engineers, and other data scientists to integrate predictive and prescriptive models with web-based applications
• Research algorithms in machine learning to identify viable approaches to meet business requirements
• Apply machine learning methods, such as natural language processing (NLP), computer vision, regression, clustering, classification, and deep learning
• Design solution prototypes that connect to data sources and deploy through services, such as service functions in web applications or application programming interfaces (APIs)
• Become familiar with DevSecOps principles to continuously deliver high-quality software
• Work with Docker to develop and deploy containerized versions of models
• Participate in design and code reviews, and collaborate with a strong, passionate engineering team
• Provide input to UX/UI designers and front-end application developers on how to effectively deliver model outcomes to users
• Interface with customer stakeholders to provide technical explanations and support

• 2024 Master's degree in Data Science, Engineering, Computer Science, Operations Research, Mathematics, Information Technology or related discipline. Quantitative coursework highly preferred.
• This program is designed for candidates with approximately 1-5 year's relevant work experience, and Spring 2024 graduate degrees in Engineering, Data Science, Mathematics, and/or technical related fields.
• Proficiency in various data processing and data analysis tools, computer spreadsheets, and database programs.
• Comfortable working with agile teams, developing prototypes and functionality in short development sprints
• Ability to work independently and collaborate effectively with a project team in an agile research and development environment
• Comfortable using Atlassian products, including JIRA, Bamboo, Confluence, FishEye, Crucible, and Bitbucket
• Experience or exposure working with tools including object-oriented programming (Python, Java), computational analysis tools (R, MATLAB), and associated data science libraries (scikit-learn).
• Excellent oral and written communication skills; ability to compose and write a variety of internal and external general business documents, reports, and presentations.
• Strong interpersonal and listening skills; ability to develop and maintain professional relationships within LMI and with its clients.
• Strong ability to prioritize projects and meet deadlines set by project leader.
• Ability to obtain security clearance is required.
• Ability to communicate complex concepts to both technical and business-focused audiences
• Familiarity or desire to excel with modern programming languages appropriate for machine learning prototyping; Python is preferred, but experience with other languages such as Java, C++, C#, JavaScript and R demonstrate the necessary ability
• Familiarity with the underlying mathematics of machine learning
• Knowledge of data structures and data management principles, methods, and tools
• Desire to explore machine learning frameworks and libraries, such as scikit-learn, TensorFlow, and Spark ML
• Ability to work with integrated development environments, such as Jupyter, JupyterLab, JetBrains IntelliJ IDEA, JetBrains PyCharm, JetBrains CLion, and Visual Studio Code
• Ability to collaborate with a team that develops applications using web development frameworks, such as Angular (1.x/2+), React, and Ember, and server frameworks, such as Node.js and Express.js
• Ability to consume or interface with cloud computing and storage services, including Amazon Web Services (AWS), Microsoft Azure, or Google Cloud
• Familiarity or desire to become familiar with containerization technologies, such as Docker, Kubernetes, Amazon Elastic Container Service (ECS), and Amazon Elastic Kubernetes Service (EKS)