Innovation Analyst Jobs (NOW HIRING)

Job Description – AI Innovation Analyst

Roofing Corp of America (RCA) is a subsidiary of FirstService Corporation, a North American leader in property services. RCA provides roofing services across 29 branch locations in the United States.

The AI Innovation Analyst is a hybrid business, technology, and project execution role responsible for identifying, evaluating, prototyping, implementing, and communicating practical AI use cases across the organization. The role collaborates with executives, business unit leaders, functional managers, frontline staff, IT, Security, Data, and external vendors to turn AI ideas into well‑defined, secure, measurable solutions. It combines business analysis, project management, AI technical knowledge and innovation catalysis.

The AI Innovation Analyst transforms AI from an emerging technology into a practical, secure, and measurable business capability by working across all levels of the organization—from C‑level leaders to frontline staff—to identify opportunities, shape use cases, coordinate pilots, support technical enablement, promote responsible AI use, and help RCA safely scale AI‑driven innovation enterprise‑wide.

• Identify high‑value AI use cases with business users
• Translate business needs into AI solution requirements
• Facilitate AI workshops with executives, managers, and staff‑level employees
• Support development and configuration of AI prototypes and pilots
• Coordinate AI projects from intake through pilot and production readiness
• Help ensure AI solutions meet RCA security, governance, and data access requirements
• Build prompt templates, AI playbooks, and user enablement materials
• Track AI adoption, outcomes, risks, issues, and lessons learned
• Serve as a practical translator between business teams, IT, Security, Data, vendors, and leadership

• Bachelor’s degree in Business, Information Technology, Computer Science, Data Analytics, Engineering, Cybersecurity, or a related field; equivalent experience may be considered
• 4+ years of experience in business analysis, project management/coordination, technology implementation, data/analytics, automation, innovation, or digital transformation
• Demonstrated interest in and working knowledge of generative AI, automation, analytics, or enterprise AI tools
• Experience gathering requirements, documenting workflows, facilitating stakeholder discussions, and translating business needs into solution requirements
• Experience coordinating cross‑functional projects with business, technical, and leadership stakeholders
• Ability to work with both senior executives and staff‑level users in a clear, credible, and practical manner
• Strong analytical skills with the ability to assess business value, feasibility, risk, and adoption considerations
• Excellent written and verbal communication skills
• Strong organizational skills and ability to manage multiple pilots, tasks, stakeholders, and deadlines
• Working knowledge of Microsoft 365 tools, SharePoint, Teams, Excel, PowerPoint, and collaboration platforms
• Ability to learn new tools quickly and explain them to others in simple, practical terms

• Experience with multiple AI or automation platforms such as ChatGPT Enterprise or Business, Microsoft Copilot, Claude / Claude Code, Azure AI, Power Automate / Power Apps, AI‑enabled SaaS tools
• Experience creating prompts, GPTs, AI assistants, automations, dashboards, or workflow prototypes
• Familiarity with AI concepts such as LLMs, RAG, AI agents, prompt engineering, embeddings, APIs, and human‑in‑the‑loop workflows
• Familiarity with AI security concepts such as data oversharing, prompt injection, hallucination, DLP, least privilege, audit logging, and approved tool governance
• Experience working in construction, field services, commercial services, industrial operations, or multi‑business‑unit organizations
• Experience supporting M&A integration, operational standardization, or enterprise transformation programs
• Familiarity with business systems such as ERP, CRM, field service, estimating, service management, or ticketing platforms

• Understands business processes quickly
• Asks strong discovery questions
• Documents workflows and requirements clearly
• Identifies root causes, not just symptoms
• Converts business needs into actionable use cases

• Organizes work into plans, tasks, owners, deadlines, and risks
• Keeps stakeholders aligned
• Tracks issues and follows through
• Communicates status clearly
• Escalates blockers early

• Experiments safely with AI tools
• Understands practical AI capabilities and limitations
• Can build simple prototypes or demos
• Learns emerging tools quickly
• Knows when to involve deeper technical resources

• Understands why data access, privacy, identity, logging, and approval controls matter
• Recognizes high‑risk use cases
• Supports responsible AI practices
• Helps users avoid unsafe or unapproved AI usage

• Can speak credibly with executives about business value
• Can speak practically with staff about daily workflow pain points
• Can translate between business, IT, Security, Data, and vendor teams
• Builds trust with users who may be unfamiliar with AI

• Looks for practical ways to improve how work gets done
• Balances creativity with control
• Focuses on measurable outcomes
• Challenges assumptions constructively
• Turns ideas into structured pilots

• Use Case Pipeline – Number and quality of AI use cases captured, documented, and advanced
• Stakeholder Engagement – Participation from executives, managers, and staff‑level users in AI discovery and pilots
• Pilot Execution – Pilots delivered with clear scope, timeline, success metrics, and lessons learned
• Business Value – Measured productivity, cycle‑time, quality, revenue, margin, or risk improvement
• AI Adoption – Growth in use of approved AI tools, templates, and workflows
• Governance Compliance – Use cases documented, reviewed, approved, and inventoried according to RCA standards
• Security Awareness – Reduction in unapproved AI usage and improved understanding of responsible AI practices
• Enablement Impact – Training participation, prompt library usage, and user satisfaction
• Portfolio Visibility – Accurate tracking of AI ideas, pilots, tools, owners, costs, risks, and outcomes