Innovation Analyst, Information Technology

Laura Canada’s Innovation team is part of the IT organization and helps identify, evaluate and advance opportunities that can create meaningful business value, including opportunities enabled by AI and emerging technologies.  Working across business and technology teams, we bring structure to complex problems, validate opportunities through research, analysis and experimentation, and develop evidence-based recommendations for investment. 

We are looking for an experienced, highly analytical problem solver who can turn ambiguity into clear decisions and measurable outcomes. You will lead discovery activities, develop business cases and financial models, establish success measures, and design experiments and prototypes that test the underlying assumptions and value of an opportunity. In our team, experimentation is hands-on: you will build working prototypes with AI-assisted tools, put them in the hands of business users, and iterate rapidly, because real usage is the strongest evidence a business case can have. 

You will work closely with business sponsors, Engineering and the broader Information Technology team. Innovation leads opportunity discovery, product thinking, experimentation and value validation, while production-grade solutions are designed and delivered through our established engineering, governance and operational processes. 

Your work spans the team’s full portfolio: decision and opportunity analysis, experimentation and prototyping, solutions configured on our enterprise platforms, and cross-functional builds with Engineering. Success in this role requires strong business judgment, quantitative and analytical capability, intellectual curiosity and the ability to communicate complex findings clearly. You will be expected to identify promising ideas, determine whether they are viable, valuable and appropriate to advance, and measure whether the intended outcomes are ultimately achieved. 

Key Responsibilities 

Frame ambiguous business problems into structured plans and testable hypotheses. 

Conduct root-cause, process and opportunity analysis to support decisions across departments. 

Build financial and operational models with clear assumptions, and develop credible business cases covering costs, benefits, ROI, payback and total cost of ownership. 

Establish baselines, targets and measurable KPIs before a solution is piloted, and quantify and track benefits realization once it ships. 

Design and run experiments and pilots with explicit success, failure and exit criteria, including working prototypes and AI-assisted tools built directly with business teams, iterated quickly from concept to validated version. 

Assess multiple solution options and develop evidence-based recommendations; translate business needs into clear requirements and executive-ready decision materials. 

Work confidently with data: validate its quality, and challenge AI-generated analysis before relying on it. 

Evaluate AI opportunities in the context of business value, risk, privacy, security and operational sustainability. 

Manage your own initiatives. You own their progress, coordination and outcomes: scope, plan, stakeholders, risks and delivery, within our delivery and governance model. Ownership here means accountability for results, not doing everything yourself. 

Partner with business sponsors, Engineering and operational teams to ensure what we validate gets built, adopted and measured. 

Communicate at every level, turning complex work into concise, executive-ready insights and recommendations. 

Who You Are 

A problem solver by instinct. You won’t always know the answer up front, but you can come up with several good ways to get to it. 

Strong business and commercial judgment, with the discipline to distinguish an interesting idea from a valuable and scalable opportunity. 

Intellectually curious and comfortable with constructive challenge: you test assumptions and change direction when the evidence says so. 

Analytical and structured, with real attention to accuracy and quality: your work is clear, organized and easy to follow. 

Fast learner, self-motivated. You pick up new domains, tools and concepts quickly and don’t wait to be told what to do next. 

Hands-on. You are just as comfortable doing the work yourself, whether digging into data or building a prototype, as you are presenting to executives. 

Able to influence without formal authority, across business and technical teams. 

A strong sense of ownership: you take full responsibility for your initiatives, including outcomes, deadlines and quality. 

Qualifications & Skills 

AI fluency (required). Beyond prompt engineering and tool familiarity: hands-on comfort using AI to analyze, build and automate, and the ability to evaluate AI capabilities, output quality, limitations, risks, controls, costs and measurable business impact. Experience building AI agents or AI-assisted applications is a strong asset. 

Analytical toolkit. Strong modeling and data-analysis skills, and the ability to use AI to analyze data and build what you need, while validating what it produces. 

Experience. Several years in consulting, business analysis, product or project-based problem solving. Experience in retail, e-commerce, consumer products, manufacturing or another complex, customer-facing operating environment is an asset. 

Education. Relevant post-secondary education, professional certification or equivalent practical experience. 

Project management. Proven ability to plan, structure and lead your own projects without a dedicated project manager. Familiarity with agile ways of working is an asset. 

Languages. Fluently bilingual in French and English.