Decision Modelling Specialist

Job Title: Decision Modelling Specialist

Location: Winnipeg, Toronto or London (Hybrid)

Estimated Duration: 3 Months

Any specific tools/skillset: 

• Strong in data analysis Ability to bridge technical acumen with business intent Experience working with enterprise level business rules Experience translating business requirements to decision models and data models
• Post-secondary education in Computer Science, Engineering, Business, or equivalent combination of training and experience
• 3–5 years of experience in decision modelling, rules analysis, business analysis, or related roles (5+ years is an asset)
• Proven ability to bridge business and technology perspectives and translate requirements into structured, logical models
• Hands-on experience working with business rules, decision tables, or logic-based design approaches
• Strong understanding of how to structure decisions for reuse, scalability, and maintainability
• Experience working with business stakeholders to clarify intent, define outcomes, and validate solutions
• Strong analytical thinking and problem solving skills, with the ability to break down complex problems into structured components
• Understanding of data structures and how decisions interact with enterprise data models
• Strong communication, collaboration, and relationship-building skills across business and technology teams
• Ability to work in cross functional teams and adapt to evolving priorities
• Growth mindset with a willingness to learn and refine decision modelling approaches

What will set you apart:

• Experience with decisioning or rules platforms (e.g. IBM ADS or IBM ODM)
• Familiarity with structured decision modelling frameworks and approaches (e.g., DMN)
• Experience in financial services or insurance domains
• Exposure to automation capabilities such as workflows, case management, or intelligent document processing
• Experience defining or applying modelling standards, governance, and reusable frameworks
• Ability to influence and guide teams toward consistent decision modelling practices
• Experience working within enterprise-scale transformation or capability build outs

Role profile description: 
Our Business Automation Technology Solutions team is a forward-thinking team delivering solutions that transform business operations. We work closely with multiple business units and technology teams to build scalable and efficient automation capabilities across workflows, case management, intelligent document processing, and enterprise decisioning.

We are seeking a Decision Modelling Specialist to support the Enterprise Rules and Decisioning Capability build out. This role will work closely with business partners, delivery teams, and engineering teams to design, model, and operationalize business decisions that drive automation and improve outcomes across the organization.

This is a specialist role focused on bridging business intent and technical execution. Unlike traditional Business Systems Analyst or developer roles, this position is centered on structuring, modeling and optimizing decisions—ensuring business logic is reusable, scalable, and aligned to enterprise standards.

What you will do:

• Support the build-out of the Enterprise Rules and Decisioning capability – including defining the strategy, how we operationalize and how we scale
• Own the end-to-end decision lifecycle, including intake, modelling, validation, deployment alignment, and continuous optimization
• Work with business stakeholders and SMEs to define decision intent, success criteria, and measurable outcomes (e.g., accuracy, latency, straight through processing)
• Identify and extract decision opportunities from business processes, legacy implementations, and subject matter expertise
• Re-engineer existing rules by identifying duplication, inconsistencies, and gaps and refining them into structured, reusable decisions
• Translate business requirements into structured decision models, including decision tables, decision flows and reusable rule components
• Apply strong decision modelling principles, ensuring solutions are designed for reuse, scalability, and maintainability across the enterprise
• Define and validate inputs, outputs, and data structures aligned with enterprise data models
• Decompose complex logic into modular decision components, clearly defining boundaries between decisions, workflows, and calculations
• Establish decision hierarchies, including top level decisions and supporting sub decisions
• Convert business rules into structured conditional logic that can be implemented within decisioning platforms
• Collaborate closely with engineering teams to ensure decision models are implementable, performant and aligned to platform capabilities
• Partner with stakeholders to validate decision accuracy and ensure alignment to business intent
• Define and maintain modelling standards including naming conventions, versioning and governance practices
• Monitor decision effectiveness and identify opportunities for optimization, reuse and continuous improvement
• Contribute to the broader automation ecosystem, ensuring decisions integrate effectively with workflows, case management, intelligent document processing, and related capabilities
• Provide mentorship and guidance to peers and junior team members on decision modelling practices and standards