Data Operations Intern (Summer 2024)

Overview

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 currently full-time telework with the ability to periodically work out of our Tysons, VA HQ*

LMI has been named a 2024 Campus Foward Award Winner! This Award recognizes excellence in early career hiring, celebrating the teams that embrace innovative recruiting strategies, care deeply about the candidate experience, are making significant investments in DEIA, and are supporting the next generation of talent through impactful internships and entry-level programs.

Responsibilities

• 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

Qualifications

• Currently enrolled in a undergrad or graduate program
• Pursuing a post-graduate or undergrad degree in engineering, mathematics, computer science, modeling and simulation, operations research, or related technical discipline
• Must be able to work for a minimum of 10 weeks beginning in May or June of 2024
• 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
• Ability to think critically to propose tractable solutions to complex problems
• Effective written and verbal communication skills
• 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)