Designing a repeatable demand-generation system across distribution channels - ON-1240

Project type: Innovation
Desired discipline(s): Engineering - computer / electrical, Engineering, Computer science, Mathematical Sciences
Company: AllMind AI Canada Inc
Project Length: 4 to 6 months
Preferred start date: As soon as possible.
Language requirement: English
Location(s): Kitchener, ON, Canada
No. of positions: 1
Desired education level: Undergraduate/BachelorRecent graduate
Open to applicants registered at an institution outside of Canada: No

About the company: 

AllMind is an AI-native research platform for institutional investors. Analysts at asset managements, hedge funds and sell-side desks spend more time hunting across various platforms like Bloomberg than they spend forming a view. AllMind collapses that into a single workflow: an intelligence layer connecting a firm's internal documents and models to external market data, with finance-trained AI agents handling the retrieval, extraction and drafting that sit underneath every memo and model.

Describe the project.: 

AllMind sells a technical product into one of the most conservative buyer segments in the market: banks, institutional asset managers, hedge funds and sell-side research teams.

The innovation to be developed is a process innovation: a documented, instrumented go-to-market system with a repeatable output. The intern will work with the team to design it and test the system during the internship.

Main tasks:
• Segment the North American institutional market (buy-side asset managers, hedge funds, sell-side research) and define ICP criteria grounded in observed conversion data.
• Design and run structured message tests across owned channels, long-form content, LinkedIn, direct outreach, events, with stated hypotheses and defined success metrics.
• Build an attribution model connecting marketing activity to pipeline, using CRM and web analytics data.
• Document the resulting playbook so it survives the internship.

Methodology: customer and prospect interviews; competitive content and message analysis; established positioning frameworks (jobs-to-be-done, category design); structured A/B testing of message and channel; funnel and cohort analysis; attribution modelling in spreadsheets or Python.

Deliverables: a positioning framework with tested messaging; a segmented target list with qualification criteria; an instrumented channel and attribution model; and a written go-to-market playbook.

The intern works directly with the team and co-founders. This is not a support role rather will allow the intern to have individual responsibilities and hands-on experience.

Required expertise/skills: 

Required:
• Strong writing and communication skills. The audiences are portfolio managers and research analysts, who detect and discard marketing language instantly. Writing plainly and precisely matters more than any tool.
• Ability to learn quickly with high problem-solving skills.

Strong assets:
• Coursework or practical experience in marketing, business strategy or communications, specifically positioning, segmentation and B2B demand generation.
• Comfort with quantitative analysis: funnel and cohort analysis, spreadsheet modelling, basic attribution. The intern will be expected to defend claims with data.
• Familiarity with capital markets, asset management or investment research, finance coursework, CFA Level I, or a prior buy-side/sell-side internship.
• A previous B2B SaaS marketing or growth internship.
• Working knowledge of CRM (HubSpot or similar), web analytics, LinkedIn and X (formerly Twitter) as a distribution channel, and modern AI tooling.
• Python or SQL for analysis (useful, not required).