Senior Data Scientist
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. 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
Requirements
- 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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What This Job Offers
Job Type
Full-time
Career Level
Senior
