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.
HOW A DATA SCIENTIST WILL MAKE AN IMPACT
- 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
REQUIRED TECHNICAL SKILLS
- 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, OmniSci) 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
WHAT YOU'LL NEED TO SUCCEED
- 2+ years of related data science/statistical experience and 1+ years of software engineering or data engineering experience
- Bachelor's or Technology degree in Engineering or a related specialized area/field, OR equivalent 4 years job-related experience OR Master's degree with 3+ years of job-related experience.
- TS/SCI with Poly clearance
- Excellent organizational, coordination, interpersonal and team building skills
- Location: At Customer Site - near Tyson Corner
- US Citizenship Required
GDIT IS YOUR PLACE
- 401K with company match
- Comprehensive health and wellness packages
- Internal mobility team dedicated to helping you own your career
- Professional growth opportunities including paid education and certifications
- Cutting-edge technology you can learn from
- Rest and recharge with paid vacation and holidays