Senior AI Business Analyst, M&A

Banyan Software•Toronto, ON

9h•CA$130,000 - CA$170,000•Hybrid

About The Position

Banyan Software is seeking a Senior AI Business Analyst to join their M&A investment team. This role is critical for enhancing the speed, sharpness, and intelligence of M&A processes through AI and data science initiatives. The analyst will act as a translator and builder, bridging deal mechanics and technical capabilities, and partnering with the central AI & Data Science team to leverage vast amounts of data. The position is hybrid and involves three key functions: AI strategist, data science translator, and builder/operator, all applied within the investment team. The goal is to contribute to an end-to-end system that grows in value with each new opportunity and operating company data set.

Requirements

Shipped real AI tools (LLMs, retrieval, or agentic workflows applied to business problems).
Ability to prototype and deliver useful AI tools directly to users.
6 to 10 years of experience in analytics, strategy, finance, or product.
At least 3 years in AI, ML, or data science.
Bachelor's degree in a quantitative, business, or technical field.
Working command of machine learning concepts, model evaluation, data quality, and AI limitations.
Strong SQL.
Working Python or R for exploration.
Command of Excel and modern BI tools (Looker, Power BI, or Tableau).
Strong financial and commercial acumen.
Ability to build a credible business case in a spreadsheet and explain it clearly.
Ability to explain a model to an executive and translate their questions into analysis.
Curiosity, humility, and the ability to push back.
Genuine interest in the work of the people supported.

Nice To Haves

Master's degree.
Deal-side experience (M&A, IB/PE, ideally in software, SaaS, or vertical market software).
Embedded analyst or business partner experience (not solely on a centralized analytics team).
Track record of measuring AI or data science impact in production, not just pilots.

Responsibilities

Embed as a core member of the investment team and own the process, learning the data, systems, KPIs, and pain points to act as the investment systems architect.
Architect the data foundation for an AI-native M&A process, connecting data across the transaction lifecycle.
Build novel tools on top of acquisition datasets to price deals, speed up diligence, and surface targets.
Identify where AI and data science can most impact transaction processes and sequence the work by impact, effort, and risk.
Develop the ROI case for AI initiatives, defining success metrics, sensitivities, and potential failure points.
Translate business problems into requirements for AI/data science engineers and interpret model outputs for actionable decisions.
Drive adoption of built tools by training the team, designing workflows, and measuring usage and impact.
Set patterns by defining and tracking KPIs for shipped tools, and share learnings across the AI & Data Science group.