Senior Data Scientist

GormatAnnapolis Junction, MD

About The Position

Gormat is seeking a candidate who possesses and applies a comprehensive knowledge across key tasks and high impact assignments. The ideal candidate is able to plan and lead major technology assignments, evaluate performance results, and recommend major changes affecting short-term project growth and success. The candidate will function as a technical expert across multiple project assignments and may supervise others.

Requirements

  • Degree from an accredited college or university in System Engineering or related discipline and one of the following: 10+ years of experience with a Master's degree, 12+ years of experience with a Bachelor's degree, 16+ years of experience with Associate's Degree or HS Diploma
  • Bachelor's degree in a relevant technical field with 8 years of experience; Master's degree in a relevant technical field with 5 years of experience; 4 years additional experience will be considered in lieu of degree
  • Advanced proficiency in programming languages commonly used for data engineering (e.g., Python, Java, Scala)
  • Demonstrated expertise in designing, developing, and optimizing data pipelines for large-scale enterprise environments
  • Proven experience with corporate dataflows and developing data parsers for extremely large datasets
  • Extensive experience with various database technologies including graph databases (e.g., Neo4j), SQL databases (e.g., PostgreSQL, MySQL), NoSQL databases (e.g., MongoDB, Cassandra), and vector databases
  • Familiarity with cloud platforms (AWS, Microsoft Azure) for data storage and processing
  • TS/SCI with polygraph is required.

Nice To Haves

  • Experience with data governance, data security, and compliance best practices
  • Familiarity with big data technologies such as Hadoop, Spark, or Kafka.
  • Experience with data warehousing concepts and tools
  • Continuous learning mindset to stay abreast of cutting-edge data engineering and AI advancements
  • Understanding of machine learning concepts and their implications for data infrastructure
  • Excellent communication and interpersonal skills, with the ability to effectively collaborate with cross-functional teams
  • Ability to translate complex data requirements into actionable engineering solutions

Responsibilities

  • Develop, and maintain robust and scalable data pipelines for enterprise AI applications including defining appropriate data model concepts
  • Develop high-performance data parsers for extremely large and complex datasets
  • Implement and manage various database systems, including graph, SQL, NoSQL, and vector databases
  • Collaborate with AI/ML engineers and data scientists to understand data requirements and optimize data access and retrieval for AI models
  • Ensure data quality, integrity, and security across all data storage solutions
  • Support the deployment and maintenance of AI applications by providing expert data engineering capabilities
  • Familiarity with AI concepts in the context of data storage, access, and retrieval
  • Continuously optimize data infrastructure for performance, cost-efficiency, and scalability
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