Data Scientist Co-op

MORSE Corp is seeking Data Scientist co-ops to help develop analysis and application software for artificial intelligence and machine learning applications. Experience with a broad range of development stacks is highly desired. Candidate should be a highly motivated self-starter with good communication skills, and should be able to work in an iterative and agile development style. If you have a broad set of data science and software skills, and want to make an impact helping deploy AI solutions to our customers in the Dept of Defense, then we are interested in you!

Responsibilities

Prepare, manage, and analyze AI data using Python; Perform data analysis tasks, including understanding performance metrics, understanding the impact of different metadata characteristics on model performance, building tools for simulating model outputs to be used in operator experiments; Create data visualizations for presenting and communicating results and solutions; Assist with the development, execution, and testing of Machine Learning models; Design and build analysis and application software using Python; Collaborate with cross-functional teams to define, design, and ship new features; Continuously discover, evaluate, and implement new technologies to maximize development efficiency

Requirements

US Citizenship required and ability to obtain a US Security Clearance; Working towards a BS or BA degree in Computer Science, Data Science, Engineering, Applied Mathematics, Physics, or a related quantitative subject; Python proficiency; An interest in Artificial Intelligence, Machine Learning, Computer Vision, GenAI, LLMs, and other data types; Experience performing statistical analyses and building data visualizations; Solid understanding of version control systems (we use Git); Good communication skills and the ability to have fun when working; Highly motivated self-starter; Ability to work in an iterative and agile development style

Nice to have

Experience with a broad range of development stacks; Experience with third-party data science libraries such as scikit-learn, pandas, numpy; Exposure to tools like Spark, PySpark, Docker, or Docker-compose