Data Scientist - TS/SCI w/Poly

Data Scientist The Data Scientist will deploy, fine-tune, and monitor production machine learning models in a production environment. Additionally, they will provide support in the areas of data extraction, transformation and load (ETL), data mapping, analytics, operations, databases, and maintenance of data and associated systems. As a member of the team, candidate will work in a multi-tasking, quick-paced, dynamic, process-improvement environment that requires experience with the principles of data science, data modeling, data mapping, data testing, data quality, and documentation preparation. This is a mission focused role requiring experience with deploying models in a production environment against real-time collection. Create and maintain custody of production machine learning models across a variety of tasks, including but not limited to audio extraction, object recognition, Natural Language Processing (NLP), and other generic classification tasks. Optimize existing machine learning services to better utilize current GPU capabilities and assist with road mapping future GPU requirements. Deploy machine learning models against streaming data, designed to provide near-real time analytics to augment decision making. Improve data architecture decisions with data engineers to better stage data for continuous training models in production. Provide support in the areas of data extraction, transformation and load (ETL), data mapping, analytics, operations, databases, and maintenance of data and associated systems. Demonstrated experience with the following: Python, Cuda, Kubernetes, CI/CD. Apache Kafka, REST architecture, Open-AI, LLMs, NLP, YOLO/Object Recognition, Whisper/Audio processing. Demonstrated experience translating data insights into tools or analytic capabilities that inform operational decisions and/or improve processes. Demonstrated experience with relational databases (SQL, Oracle) and NoSQL databases (Elasticsearch, Neo4J, Redis). Demonstrated experience with GPU processing. Demonstrated experience applying machine learning methodologies to build high-quality prediction models. Familiar with servers operating systems; Windows, Linux, Distributed Computing, Blade Centers, and cloud infrastructure. Familiar with database methodologies. Familiar with Source code management and integration (ex - GitHub/GitLab, Jenkins, RunDeck). Familiar with Data Science frameworks such as Keras, Tensorflow, or Theano. Ability to work well in a fast-paced, constantly evolving work environment with a focus on continual process improvement and a proactive approach to problem solving. 10+ years of related data science/statistical experience and 2+ years of software engineering or data engineering experience. Bachelor's or Technology degree in Engineering or a related specialized area/field, OR equivalent 4 additional years job-related experience. TS/SCI with Polygraph clearance. Excellent organizational, coordination, interpersonal and team building skills. Location: At Customer Site - near Tyson Corner. General Dynamics