Workplace AI Business Analytics Specialist

Salary Range: 51000 to 84500 (Currency: CAD) (Pay period: per-year-salary)

AI Research (30%)

• Conducts needs assessments across departments to identify opportunities where AI tools can improve operational efficiency or research outcomes.
• Monitors emerging AI technologies and evaluates their relevance to Alimentiv's operational context.
• Develops roadmaps that align AI opportunities with organizational priorities and realistic implementation timelines.
• Synthesizes industry trends into actionable recommendations tailored to Alimentiv's business environment.
• Evaluates AI platforms and tools against defined use cases, documenting findings in structured assessments.
• Develops lightweight solution prototypes to validate feasibility before full implementation is pursued.
• Prepares business cases that articulate the value and feasibility of proposed AI initiatives for non-technical stakeholders.

User Enablement (35%)

• Designs and delivers structured training programs that build AI proficiency across diverse teams and skill levels.
• Produces plain-language reference materials, guides, and job aids that support independent tool use.
• Facilitates workshops and demonstrations that connect AI capabilities to team-specific workflows.
• Provides hands-on support during tool rollouts to accelerate user proficiency and resolve adoption barriers.
• Identifies and addresses adoption obstacles through targeted follow-up and adjusted delivery approaches.
• Establishes communities of practice to enable peer learning and sustained engagement with AI tools.
• Monitors usage data and initiates proactive outreach where additional training or support is indicated

Solution Development (25%)

• Designs and builds proof-of-concept AI solutions that demonstrate practical value to specific business functions.
• Develops working prototypes using no-code and low-code AI platforms to illustrate how AI can be applied to real operational challenges.
• Presents and demonstrates prototype solutions to stakeholders, translating outputs into clear business value.
• Builds demonstrations and prototypes using no-code and low-code AI platforms; production development and system integration remain the responsibility of technical IT and development teams.
• Gathers departmental requirements and communicates them to technical teams in plain language.
• Coordinates cross-functional stakeholders to ensure AI tool configurations align with operational workflows.
• Develops standard operating procedures that integrate AI tools into established team workflows.

Performance Measurement (10%)

• Establishes success metrics that capture both adoption rates and measurable business impact.
• Analyzes usage and performance data to assess initiative effectiveness and identify areas for improvement.
• Prepares reports that communicate AI initiative outcomes clearly to leadership audiences.
• Conducts post-implementation reviews to capture lessons learned and apply findings to future rollouts.

QUALIFICATIONS

3+ years of related experience
(Honours) Bachelor’s degree
Fluent in English (verbal and written)
Ability to communicate complex or technical concepts clearly to non-technical audiences (verbal and written)
Demonstrated ability to build effective working relationships across all organizational levels, including frontline staff and senior leadership
Experience designing and delivering training programs for diverse adult learners
Knowledge of change management principles and technology adoption frameworks
Ability to identify underlying user needs and develop practical, targeted support solutions
Experience producing user documentation, guides, and job aids that reduce barriers to tool adoption
Proficiency with no-code and low-code platforms (e.g., Microsoft Copilot Studio, Power Automate, Claude.ai) to configure and demonstrate AI-powered workflows without custom development
Ability to develop functional proof-of-concept solutions demonstrating AI applicability to specific business problems
Familiarity with prompt engineering and understanding of large language model capabilities and limitations
Ability to define and communicate the boundary between enablement-level prototyping and production development requiring IT or developer involvement
Strong cross-functional collaboration skills and ability to align stakeholders around shared objectives
Ability to interpret adoption metrics and usage data to prioritize support efforts
Working knowledge of AI tools sufficient to guide end-user adoption (deep technical expertise not required)
Familiarity with data privacy principles and responsible AI use in regulated environments
Experience in clinical research or healthcare is considered an asset