Senior Data Scientist

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

• 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

• 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