Senior AI Business Analyst - Operations
$130,000–$170,000 year
HybridToronto, Ontario, Canada
Job Summary
Embed inside a functional vertical (Finance, M&A, Business Development, HR, Legal, or Operations) to learn workflows, KPIs, and pain points. Identify and prioritize AI and data science opportunities that move function metrics, then build clear, ROI-driven business cases with defined success metrics and sensitivities. Translate business problems into well-scoped requirements for engineers and interpret model outputs into actionable decisions for stakeholders. Partner with functional leaders on roadmap prioritization, drive tool adoption through training and workflow design, and measure real impact via adoption and outcome tracking. Define and monitor KPIs for every initiative, including model performance, time saved, and dollar impact.
Required Qualifications
- 6 to 10 years of experience as a business analyst, strategy consultant, FP&A or finance analyst, BD or M&A analyst, product manager, or data science partner
- At least 3 of those years involved AI, ML, or data science work
- A bachelor's degree in a quantitative, business, or technical field
- Working knowledge of machine learning concepts, model evaluation, data quality, and the limits of AI
- Strong comfort with SQL
- A working familiarity with Python or R for data exploration
- Strong Excel and modern BI tools (Looker, Power BI, Tableau, or similar)
- Strong financial and business acumen
- Excellent communication skills
- Track record of being trusted by a non-technical functional team
- Curiosity, judgment, and humility
- Typically 2 to 3 days per week in our Toronto office
- Occasional travel to functional team offsites
Desired Qualifications
- A master's degree
- Direct experience inside Finance, M&A, or Business Development
- Bonus for software, SaaS, or vertical market software environments
- Hands-on work with LLMs, retrieval systems, or agentic workflows applied to internal operations
- Prior experience as an embedded analyst or business partner, rather than a member of a fully centralized analytics team
- A track record of measuring AI or data science ROI in production, not just in pilots
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