Data Science Software Engineer

Laurel, MD

TS/SCI + FS Poly

What You'll be Owning

GRVTY is seeking a with a TS/SCI + Poly clearance (applicable to this customer) to join one of our top projects in .

• The Data Science Software Engineer shall develop, enhance, and prototype compliance and business processing analytics and tools. They will also develop new methods for automating compliance functions and improve existing methods. Additionally, the Engineer will investigate, integrate, and test compliance modernization Machine Learning/AI algorithms and research proof-of-concepts in the RD environment. Lastly, the Engineer will develop models and implement appropriate metrics and monitoring of developed tools, functions, and data flows.

What You Must Have

• Active TS/SCI with Polygraph Clearance
• Twenty (20) years experience as a SWE in programs and contracts of similar scope, type, and complexity is required.
• Bachelor’s degree in Computer Science or related discipline from an accredited college or university is required. Four (4) years of additional SWE experience on projects with similar software processes may be substituted for a bachelor’s degree.
• Experience with Java, Scala, and Python
• Experience with Lucene, JEXL, SQL, JSON
• Random Forest and ability to do feature development for Random Forest
• Experience with Machine Learning Model building and monitoring
• Experience developing in a Linux operating environment
• Experience with Ghostmachine (Map/Reduce)
• Experience with GM Learn
• Experience with Jupyter Notebooks
• Experience with IntelliJ and/or Eclipse
• Experience with Git/Gitlab and/or Stash/Bitbucket
• Experience with Jira
• Experience with Confluence
• Experience with Scikit-learn
• Agency Compliance standards, policies, and authorities
• Experience with Agency corporate systems
• Experience with documentation and reviewing documentation

What Would be Nice to Have

• Data Science skills/background
• Experience with AWS
• Experience implementing ML systems
• Experience with Spark
• Exploratory Data Analysis (EDA)
• Agentic AI
• Large Language Models (LLM)
• Machine Learning Feature Development
• Other Machine Learning models and techniques

#LI-BPJ

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