Senior Data Scientist & Modeler

The Senior Data Scientist & Modeler position is responsible for designing and maintaining the data structures that power business applications, analytics platforms, and emerging AI capabilities. This role ensures that data is well-organized, high-quality, and ready for use in reporting, machine learning models, and automation. The role also develops ontologies, knowledge graphs, rules or other symbolic models, or insights into specific business processes or domains.

Requirements

• Designs and maintains conceptual, logical, and physical data models.
• Builds and operationalizes data solutions including transformations, cleansing, and quality improvements.
• Translates business requirements into scalable data models supporting analytics and AI use cases.
• Creates and implements data models and ontologies to support knowledge representation by organizing large volumes of data into knowledge structures
• Develops and maintains documentation for knowledge graphs as well as knowledge engineering processes and systems
• Tests and evaluates new models to identify areas of improvement and optimization
• Analyzes existing information models and standards and identifies their advantages and disadvantages
• Creates ERDs, data flow diagrams, and other model documentation.
• Collaborates with data engineers, AI engineers, and DBAs to implement models across databases, warehouses, and data lakes.
• Applies data modeling best practices and resolve data consistency issues.
• Optimizes models for performance, security, and reliability.
• Incorporates data governance, security, and quality standards.
• Prepares data structures for ML pipelines, feature stores, and LLM-ready datasets.
• Supports AI teams with data models for RAG pipelines and semantic/knowledge graph architecture.
• Collaborates with data scientists and analysts to optimize models and algorithms for data quality, security, and governance
• Integrates data from different sources, including databases, data warehouses, APIs, and external systems
• Ensures data consistency and integrity during the integration process, performing data validation and cleaning as needed
• Optimizes data pipelines and data processing workflows for performance, scalability, and efficiency
• Implements data quality checks and validations within data pipelines to ensure the accuracy, consistency, and completeness of data
• Takes authority, responsibility, and accountability for exploiting the value of enterprise information assets and of the analytics used to render insights for decision making automated decisions and augmentation of human performance
• Works with board members and other executives to establish the vision for managing data as a business asset
• Establishes the governance of data and algorithms used for analysis, analytical applications, and automated decision making.

Benefits

• Competitive benefits
• Growth opportunities
• Generous performance-based bonuses
• 12% 401(k) match
• Comprehensive health, dental, and vision insurance
• Tuition reimbursement
• Professional development