Lead and mentor an interdisciplinary team consisting of both developers and researchers
Assemble large, complex sets of data to support AI/ML algorithm implementation
Build required infrastructure for optimal extraction, transformation and loading of data from various data sources
Curate and maintain data that is stored in support of metrics and evaluation
Implement Artificial Intelligence/Machine Learning algorithms
Identify, design, and implement internal process improvements including re-designing infrastructure for greater scalability, optimizing data delivery, and automating manual processes
Use Agile methodologies to develop software

B.S. in data science, AI/ML, computer science, or related field
Minimum 10 years of relevant experience as a Data Engineer/Scientist
Active TS/SCI with Polygraph security clearance
Experience developing data pipelines and normalizing data with canonical Python packages ( e.g. NumPy, Pandas, Polars)
Experience contributing on a team using version control ( e.g. git, GitLab, Bitbucket)
M.S. or PhD in data science, AI/ML, computer science, or related field (Desired)
Experience with Gitlab, DevSecOps utilizing test-driven development, containers, ( e.g. Docker, Docker Compose), cloud services ( e.g. AWS), tools for distributed computing ( e.g. Spark, Pyspark ) (Desired)
Experience leading an interdisciplinary team of researchers and software developers (Desired)
Experience with Large Language Models (Desired)
Familiarity with applying clustering algorithms and/or deep neural networks to real life problems (Desired)

Principal Data Scientist

Key skills