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Innovation Manager, R&D

Job in Exshaw, Alberta, Canada
Listing for: Clario Holdings Inc.
Full Time position
Listed on 2026-05-16
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Data Science Manager
Job Description & How to Apply Below
Location: Exshaw

Innovation Manager, R&D page is loaded## Innovation Manager, R&Dlocations:
Canada Remote time type:
Full time posted on:
Posted Todayjob requisition :
R17561

Clario, a part of Thermo Fisher Scientific, is a global leader in clinical trial endpoint technology. We are seeking an Innovation Manager, R&D to help define what comes next for Clario’s software and AI‐enabled offerings. This role sits at the intersection of market insight, emerging technology, and product strategy: you will engage with customers, industry partners, and internal stakeholders to uncover unmet needs and new revenue opportunities, with a particular focus on applying AI and automation to create differentiated value and efficiencies.

You will focus on shaping and validating opportunities: framing problems, exploring AI‐driven solution options, and creating clear, testable experiment and MVP charters. You will partner closely with AI/ML and data science teams, product management, architects, and a dedicated Product Owner who translates your concepts into backlogs for Agile Scrum teams. Your ability to connect innovative ideas to measurable business outcomes will ensure Clario continues to lead through scalable, secure, and customer‐centric solutions in regulated healthcare environments.
** What You’ll Be Doing
*** Identify and evaluate new revenue‐generating opportunities by engaging with customers, industry partners, and internal stakeholders across Clario.
* Lead discovery and concept development, turning unmet needs and early ideas into clear problem statements, opportunity briefs, and high‐level solution concepts.
* Deeply explore the AI and data space (e.g., machine learning, generative AI, computer vision, workflow automation) to identify innovations and integrations that can drive new revenue streams and operational efficiencies.
* Partner closely with AI/ML and data science teams to:  + Understand current capabilities and roadmaps,  + Brainstorm new AI‐enabled features and services,  + Assess where and how AI can be safely and effectively embedded into existing and new products.
* Define and maintain an innovation opportunity portfolio / roadmap that prioritizes concepts (especially AI‐enabled ones) based on business value, feasibility, risk, and strategic alignment.
* Facilitate ideation workshops, design sprints, and discovery sessions with AI, product, engineering, and commercial teams to refine concepts and converge on the most promising solutions.
* Collaborate with architects and senior engineers to assess technical options, constraints, and high‐level solution approaches, without directly owning coding or detailed system architecture.
* For high‐potential opportunities, define experiment/MVP charters that capture:  + The customer problem and target users,  + Key hypotheses and assumptions,  + Desired outcomes and high‐level success criteria,  + Risks, dependencies, and key metrics to observe.
* Work closely with the Product Owner to:  + Translate opportunity briefs and MVP charters into product backlogs and user stories,  + Ensure the original problem, hypotheses, and success criteria are understood by delivery teams,  + Review learnings from increments and experiments and iterate on concepts as needed.
* Analyze results from experiments, prototypes, and customer feedback to recommend whether to scale, pivot, or stop initiatives, with a focus on measurable revenue impact and efficiency gains.
* Prepare and present concise business cases and recommendations to leadership and product stakeholders, summarizing opportunity size, risks, learnings, and proposed next steps.
* Champion a culture of experimentation, learning, and “productive failure”, ensuring that insights from both successful and unsuccessful initiatives are captured, shared, and used to inform future innovation work.
** What We Look For
*** Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field; an advanced degree or MBA is a plus.
* 7+ years of experience in software, data, or product environments (e.g., engineering, solution architecture, product strategy, innovation/R&D, consulting), including time spent in discovery / early‐stage…
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