Business Operations Analyst, AI Enablement
New
CanadaFull-TimeMiddle
Salary not disclosed
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Job Details
- Experience
- 1–2 years
- Required Skills
- Project ManagementSQLBusiness OperationsData visualizationProcess improvementScripting
Requirements
- Bachelor’s degree in Business, Operations, or a related field, or equivalent practical experience.
- 1–2 years of experience in business operations, process improvement, consulting, or similar execution-focused roles (preferred but not required).
- Strong analytical and structured problem-solving skills with the ability to move between detailed execution and high-level strategy.
- Excellent communication skills with the ability to collaborate effectively across teams and clearly articulate ideas and solutions.
- Curiosity and strong interest in AI tools, automation, and modern workflow optimization techniques.
- Experience or exposure to low-code/no-code platforms (e.g., Parabola, n8n) is an asset.
- Basic familiarity with SQL, scripting, dashboards, or data tools is a plus.
- Strong organizational skills with a proven ability to manage projects from concept to completion.
- Self-starter mindset with strong ownership, reliability, and follow-through.
Responsibilities
- Analyze and map existing business workflows to identify inefficiencies, bottlenecks, and opportunities for automation or redesign.
- Design and implement improved processes using low-code/no-code tools, AI-enabled solutions, and lightweight internal systems.
- Own initiatives end-to-end, from problem definition and solution design through implementation, testing, and iteration.
- Collaborate with cross-functional stakeholders across Operations, Finance, and GTM teams to understand pain points and deliver impactful solutions.
- Build prototypes, automations, and workflow enhancements that increase speed, accuracy, and scalability of internal operations.
- Support the adoption of AI tools and “doing more with less” principles across teams through enablement and practical application.
- Continuously evaluate internal processes and propose data-driven improvements to strengthen overall operational efficiency.
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