Job Specifications
AI & Automation Business Analyst / Solution Framing Lead (Intake → MVP → Production Readiness)
Location: Toronto ON or Montreal QC ( Hybrid, 3 days onsite)
Duration: 12 months
Rates: Negotiable
Summary
Client’s Data & AI organization is seeking an experienced AI & Automation Business Analyst / Solution Framing Lead to own the front-door intake and discovery for AI, analytics, and automation initiatives. This role converts early ideas into well-scoped, measurable, delivery-ready problem statements that can move efficiently through implementation and into production. The successful candidate will be comfortable challenging assumptions (“AI for AI’s sake”), defining decision/workflow architecture (including human-in-the-loop and exception handling), and governing vendor proposals to ensure alignment with security, data access, architecture standards, and operating model.
This role is ideal for consultants with proven experience in operations/workflow transformation, solution discovery, and industrializing AI/automation from concept through production.
Key Responsibilities
1) Front-Door Intake & Discovery Lead
Lead the first client conversations and discovery workshops with business stakeholders.
Rapidly clarify business objective, current process, pain points, constraints, stakeholders, and desired outcomes.
Ensure requests are well-formed and ready to enter the delivery pipeline (clear scope, owners, value hypothesis).
2) AI / Automation Challenge Function (Fit Assessment & Myth-Busting)
Pressure-test whether AI is required or if simpler process/system changes are more appropriate.
Classify the solution approach: automation vs analytics vs GenAI (and where each belongs).
Reset expectations with stakeholders: risks, limitations, dependencies, and what “good” looks like.
3) Problem Framing & Decision Architecture
Convert ideas into structured, delivery-ready artifacts:
o Problem statement and target users
o Decision points, workflow steps, and “system of action”
o Inputs/outputs, data sources, and dependencies
o Human-in-the-loop design, exception handling, escalation paths
o KPIs, baselines, success criteria, and value hypothesis (benefits case)
4) Vendor & Solution Governance
Challenge vendor recommendations using clear requirements and evaluation criteria.
Enforce alignment with internal standards (security, RBAC/data access, architecture, auditability, operational ownership).
Prevent scope creep and ensure proof points exist for production readiness (non-functional requirements, monitoring, support model).
5) Repeatable Workflow & Executive-Ready Artifacts
Run a consistent early-stage process (end-to-end):
o Intake checklist and triage
o Discovery workshop facilitation
o Feasibility and risk screen
o Data readiness assessment
o MVP definition and roadmap
o Next-step execution plan and handoff package
Produce concise, executive-ready outputs (1–3 pages) that enable delivery teams to execute confidently.
Required Experience & Qualifications:
• 8–12+ years in Business Analysis / Product Analysis / Solution Consulting / Digital Transformation roles, with ownership of discovery-to-delivery.
• Demonstrated experience delivering initiatives into production (not just POCs), including operationalization considerations:
O Non-functional requirements, monitoring, change management, adoption, support/ownership.
• Strong understanding of automation and AI solution patterns, including:
O Workflow automation (RPA/BPM), analytics and decision support, GenAI/RAG use cases.
• Proven ability to define measurable outcomes:
OKPIs, baselines, benefits cases, value hypotheses, and success criteria.
• Experience challenging and governing vendors:
O Requirements, evaluation criteria, controls, security expectations, scope management.
• Excellent stakeholder leadership:
O Runs workshops, aligns executives and operators, communicates trade-offs clearly.
Preferred Experience (Strong Assets)
• Manufacturing / industrial operations experience (quality, maintenance, reliability, energy, production workflows), or deep corporate process automation experience (finance/AP, procurement, HR).
• Familiarity with:
o data readiness assessment and data governance fundamentals
o role-based access control (RBAC), privacy/security constraints, audit logs
o Agile delivery, stage gates, and portfolio intake models
• Experience designing human-in-the-loop workflows and exception-based operations models.
Core Deliverables (What “Good” Looks Like)
The candidate is expected to consistently produce high-quality, production-oriented artifacts such as:
Intake brief (problem, users, outcomes, constraints)
Discovery workshop output + current-state process map
Fit assessment (AI vs non-AI; solution type and rationale)
Decision/workflow architecture (including HITL and exceptions)
Data readiness checklist + key data gaps/risks
MVP definition (scope, KPIs, acceptance criteria)
Vendor evaluation rubric and chal