Senior AI Business Analyst, Mergers & Acquisitions
The Role

Senior M&A AI Business Analyst plays a critical leadership role within the Banyan M&A investment team, one of the most active software acquirors in the world. You will operate inside that team, understanding and reimagining its workflows, and executing the high-value AI and data science initiatives that make M&A faster, sharper and smarter.

You will join a world-class operation sitting on a vast quantity of high-quality data waiting to be leveraged. Think of yourself as a translator and a builder, fluent in what modern AI and data science can do and trusted by both sides to bridge deal mechanics and technical capability. Partnering with our central AI & Data Science team, you will bring real AI capability to the M&A team's biggest opportunities and help build the data foundation that powers it. Given M&A functions in between both new business development and operations, you sit at the intersection of all three groups, contributing to the architecture of a true end-to-end system that becomes more valuable with each new opportunity and operating company data set.

This is a hybrid role that blends three jobs, all applied inside our investment team:

• AI strategist: identify, prioritize, and build business cases for AI and data science that drive M&A KPIs.
• Data science translator: bridge M&A stakeholders and technical AI/ data resources. Scope models and tools, then interpret outputs in clear, decision-useful terms.
• Builder and operator: prototype and ship working AI tools directly, help the M&A team adopt them in their workflows, and measure real impact. Lean on the central AI & Data Science team for engineering support as complexity scales.

Quick Facts

Team

Technology & Data Strategy, embedded as business partner to the M&A team

Reports to

Senior Director, Technology & Data Strategy; dotted line to the Lead AI Architect

Location

Toronto, Ontario. Hybrid: typically, 3 days per week in our Toronto office

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.
What You Will Do

• Embed yourself as a core member of our investment team and own the process. Learn the data, systems, KPIs, and pain points well enough that the team leans on you as its investment systems architect.
• Help architect the data foundation for an AI-native M&A process. Connect the data that today lives in separate systems across the full transaction lifecycle, from screening through diligence to closing, with hooks into sourcing upstream and integration downstream.
• Build novel tools on top of one of the richest acquisition datasets anywhere. They price a deal, speed up diligence and surface targets before competitors see them.
• Find where AI and data science can most change how transactions get done. Then sequence the work by impact, effort, and risk.
• Make the ROI case for each one. Define what success looks like, the sensitivities, and what would make the work fail.
• Translate in both directions. Turn business problems into well-scoped requirements for our AI and data science engineers and turn model and tool outputs back into decisions the team can act on.
• Drive adoption. Train the team, design the workflows around what you build, and measure usage and real impact after launch.
• Set the patterns. Define and track KPIs for everything you ship, from model performance and adoption to time saved, decision quality and dollar impact. Share what works across the AI & Data Science group so we can reuse it in the next embedded role.

Who You Are

• You love building. You have shipped real AI tools, not just read about them. LLMs, retrieval or agentic workflows applied to business problems. You can prototype and put something useful in users' hands yourself.
• You have the background. 6 to 10 years across analytics, strategy, finance, or product, with at least 3 years in AI, ML or data science. A bachelor's in a quantitative, business, or technical field; a master's is a plus, not a requirement.
• You are technically grounded. Working command of machine learning concepts, model evaluation, data quality, and the limits of AI. You know what is possible, what is hard, and what is risky.
• You are fluent in data. Strong SQL, working Python or R for exploration, and command of Excel and modern BI tools such as Looker, Power BI, or Tableau.
• You think in business value. Strong financial and commercial acumen. You can build a credible case in a spreadsheet and explain it clearly in a one-pager.
• You translate. You can explain a model to an executive and turn their question into a well-scoped piece of analysis. The functional teams you have partnered with want to work with you again.
• You bring judgment. Curiosity, humility, and the spine to push back. You stay genuinely interested in the work of the people you support.

Bonus Points

• Deal-side experience. Direct time inside M&A or IB/PE, ideally in software, SaaS, or vertical market software.
• Embedded experience. You have worked as an embedded analyst or business partner, not just on a fully centralized analytics team.
• Production ROI. A track record of measuring AI or data science impact in production, not just in pilots.

Why Banyan

• You own the agenda, not a ticket queue. You set M&A's AI roadmap and decide what gets built.
• Built to hold forever. The tools you build are made to last and compound for years, deal after deal. We invest and operate on a permanent time horizon, free from the short-term pressure to satisfy investors each quarter.
• A front-row seat with people who do this at the highest level. You sit inside one of the most active serial acquirers in software and learn the business from the investors and operators doing the deals.
• A real AI foundation already in place. You step into a working AI-native M&A engine and take it further, building alongside a high-adoption, fast-moving team that already works this way from day one.
• Autonomy with a high bar. We trust you to make the call, and we expect you to own the outcome.
• Paid for the scope. Competitive base, performance bonus, full benefits, and meaningful long-term upside.

How to Apply

Send your resume and a short note about a time you brought AI or data science into a functional team's workflow. Tell us the impact, what made it hard, and what you would do differently next time.

We look forward to hearing from you.