Parsons is looking for an amazingly talented Data Scientist to join our team! In this role you will get to make an impact on the future success of the U.S. Cyber Command.
Design, 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
Active TS/SCI with Polygraph
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
An active Top Secret SCI w/Polygraph security clearance is required for this position.
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