Data Science Software Engineer

About the role

The Data Science Software Engineer will play a crucial role in developing, enhancing, and prototyping compliance and business processing analytics and tools for OPS Consulting. This position focuses on automating compliance functions and improving existing methods through the integration and testing of Machine Learning/AI algorithms.

Responsibilities

• Develop, enhance, and prototype compliance and business processing analytics and tools
• Investigate, integrate, and test compliance modernization Machine Learning/AI algorithms
• Develop models and implement appropriate metrics and monitoring of developed tools, functions, and data flows

Requirements

• Twenty (20) years experience as a SWE in programs and contracts of similar scope, type, and complexity
• Bachelor’s degree in Computer Science or related discipline from an accredited college or university
• Four (4) years of additional SWE experience on projects with similar software processes may be substituted for a bachelor’s degree
• US citizenship and an active security clearance required

Qualifications

• Experience with Java, Scala, and Python
• Experience with Lucene, JEXL, SQL, JSON
• Experience with Random Forest and 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

Skills

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