Join our team as a Decision Science Practitioner Consultant, a key role focused on building and maintaining robust data models for advanced analytics, AI/ML, and Generative AI initiatives. You will bridge the gap between business needs and technical implementation, creating foundational assets that drive AI-driven insights and automation across the enterprise.

This consultative position requires a strong understanding of data modeling principles and the ability to translate complex business logic into scalable, high-quality data structures. You will collaborate extensively with domain experts, data scientists, and engineers to ensure our data models effectively support diverse use cases.

Be at the forefront of AI innovation, contributing to responsible AI development and unlocking new business possibilities through data. This role offers a dynamic environment to apply your expertise in a growing field.

Collaborate with stakeholders to understand data requirements and translate them into conceptual, logical, and physical data models.

Work closely with data engineers and AI/ML practitioners to ensure data models meet downstream consumption needs.

Independently manage modeling workstreams, including requirements gathering, design, and documentation.

Document and communicate modeling decisions and best practices to both technical and non-technical audiences.

Design and maintain models for structured and semi-structured data, supporting analytics, AI/ML, and decision science.

Develop reusable models for feature engineering and decision science applications.

Enable ontology and knowledge graph modeling, transforming subject-matter knowledge into machine-readable formats.

Design data and semantic models to serve as foundational datasets for AI/ML and Generative AI systems.

Partner with AI teams to ensure models support RAG pipelines and intelligent agent workflows.

Demonstrated expertise in Data Modeling, Conceptual & Logical Design, and Semantic Modelling.

Solid understanding of Knowledge Graphs is essential for this role.

Experience with Data Science, Ontologies, AI/ML Data Enablement, and GenAI Foundations is highly beneficial.

Ability to work independently on modeling tasks, from gathering requirements to final design and documentation.

Strong communication skills to effectively convey complex technical information to diverse audiences.

Experience in designing and maintaining conceptual, logical, and physical data models for enterprise systems.

Familiarity with data governance standards, naming conventions, and design guidelines.

A Bachelor's degree in a relevant field is expected.