Senior AI Business Analyst - Operations

Banyan Software is the best permanent home for software businesses that serve specialized industries, their employees, and their customers. We are on a mission to acquire, build, and grow great companies worldwide, helping them modernize through shared AI expertise and operational discipline. The Banyan Software Foundation, endowed with $100 million in Banyan stock, leverages technology to build a greener and more equitable world.

Banyan is Great Place to Work Certified, a five-time Inc. 5000 honoree, and a top 10 company on the Deloitte Technology Fast 500. Founded in 2016 and headquartered in Atlanta, Banyan operates more than 100 portfolio companies across North America, the UK, EU, and APAC.

The Role We are hiring a Senior Business Analyst, AI & Data Science to serve as an embedded business partner to one of our internal functional teams. You will be assigned to a single functional vertical at hire:
Finance, M&A, Business Development, Human Resources, Legal, or Operations. You will spend your days inside that team, learning their workflows, surfacing high-value AI and data science opportunities, and shipping work that makes them faster, sharper, and more effective. You will report into our central AI & Data Science team and work day-to-day alongside the leaders and operators of your assigned vertical.

Think of yourself as a translator and a builder: fluent in the function's metrics and mechanics, fluent in what modern AI and data science can do, and trusted by both sides to bridge the two. This is a hybrid role that blends three jobs, all applied inside your assigned function: AI strategist: identify, prioritize, and build the business case for AI and data science use cases that move the function's KPIs.

Data science translator: bridge functional stakeholders and technical AI and data resources. Scope models and tools, then interpret outputs in clear, decision-useful terms. Operations partner: help the function operationalize AI and data tools in their workflows, drive adoption, and measure real impact.

• Team AI & Data Science, embedded as business partner to one functional vertical
• Vertical assignment Finance, M&A, Business Development, Human Resources, Legal, or Operations
• Assigned at hire based on fit and team need
• Reports to Head of AI & Data Science, with a dotted line to the functional leader
• Location Toronto, Ontario
• Hybrid: typically 2 to 3 days per week in our Toronto office, with occasional travel to functional team offsites
• Type Full-time Level Senior
• Compensation Competitive base of CAD $130,000 to $170,000 plus performance bonus and benefits. Final offer reflects experience and qualifications.

• Embed inside your assigned function (Finance, M&A, Business Development, Human Resources, Legal, or Operations). Learn its data, systems, KPIs, and pain points well enough that the team treats you as one of their own.
• Identify and prioritize AI and data science opportunities that move the function's metrics. Sequence them by impact, effort, and risk.
• Build clear, ROI-driven business cases for each opportunity. Define success metrics, sensitivities, and what would make the work fail.
• Translate business problems into well-scoped requirements for our AI and data science engineers.
• Translate model and tool outputs back into decisions the function can act on.
• Partner with the functional leader on roadmap and prioritization. Help them say yes to the right work and no to the rest.
• Drive adoption of AI and data tools inside the function. Train end users, design new workflows, and measure usage and outcomes after launch.
• Define and track KPIs for every initiative you support, including model performance, adoption, time saved, decision quality, and dollar impact.
• Stay close to the AI and data science landscape, including LLMs, agentic systems, and modern analytics tooling. Bring a clear, well-reasoned point of view to the team.
• Share what works across the AI & Data Science group so other functional partners benefit from your patterns and pitfalls.

• Finance: automate close and reporting tasks, build forecasting and scenario models, surface working capital and cost insights, build self-serve analytics for finance leadership, accelerate management reporting cycles.
• M&A: build sourcing and pipeline analytics, develop scoring models for inbound and outbound targets, structure and enrich the deal database, automate market mapping and competitive research, support deal teams with data-driven insights.
• Business Development: build lead scoring and prioritization models, analyze outbound campaign performance, automate research workflows, develop dashboards for pipeline health, surface signals that predict engagement and conversion.
• Human Resources: build workforce and attrition analytics, model hiring funnel performance and time-to-fill, benchmark compensation, surface engagement and sentiment insights, and automate repetitive HR operations.
• Legal: automate contract review and clause…