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, 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
WHAT YOU’LL NEED TO SUCCEED:
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
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
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