Data and analytics recruitment, from pipeline to production model.
A data and analytics recruitment agency for Canadian teams. From the pipeline to the model to the dashboard, we recruit the people who turn your data into decisions, screened by recruiters who can tell an engineer from a scientist from an analyst.
The stack
The data stack, from ingest to insight.
Data and AI isn’t one job. It’s a whole STACK of them, from the pipeline to the model, which is why data and analytics recruitment has to screen each layer against different evidence.
Why STACK IT
Data and analytics recruitment that tells the four jobs apart.
A data engineer and a data scientist are not interchangeable. We screen each layer for what actually makes someone effective in it.
Recruiters who speak data
Our recruiters know a data engineer builds the pipelines and a scientist builds the models, and they screen for the one you actually need.
Every candidate is real
AI-assisted interviews and inflated resumes are everywhere in this field. We meet each candidate face-to-face on video, so who you interview is who shows up.
One standard, every layer
Whether it’s a junior analyst or a senior ML engineer, the same two-reviewer screen and 90-day guarantee apply.
How we screen
One bar, held every time.
The deep role-specific rubric lives on each role page. Across the category, every search runs on the same method.
Recruiter-led screening, every time
A pile of tool names on a resume doesn’t prove someone can ship a model. We screen against real scenarios.
Two reviewers per shortlist
No candidate reaches you until a second reviewer signs off, so the bar holds on every search.
Screened to stay
Data and AI talent is in high demand and easily poached. We align trajectory and total comp so the hire sticks.
Backed by the guarantee
Permanent placements carry a 90-day replacement guarantee, and contract roles a fast backfill, at no extra cost.
FAQ
Hiring data & AI talent, answered.
Ask whether the recruiter can distinguish the four jobs that get lumped together. Data engineers build the pipelines, analysts turn the output into decisions, scientists build the models, and machine learning engineers put those models into production. A generalist desk screens all four against the same keyword list, which is how teams end up interviewing a dashboard specialist for a pipeline role. Ask who screens, whether they recruit data specifically, and what happens if the hire does not work out.
Yes, and the distinction matters more than it used to. AI and machine learning engineers are hired for production systems: models that ship, serve traffic, and get measured. Data scientists are hired for the modelling and experimentation upstream of that. Briefs that blur the two tend to stall, because the shortlist ends up split between people who can build a model and people who can run one at scale.
Across the stack: data engineers who build the pipelines, data scientists and AI engineers who build the models, and data analysts who turn it into decisions.
We look past notebook demos to what a candidate has shipped, probing pipelines, evaluation, and rigor, and we have them explain their decisions in plain terms. Building something once and running it reliably in production are different skills. Project-scoped data work often runs through contract IT recruitment when timelines are tight.
It is among the most competitive markets right now, so bands move fast and strong people field multiple offers. We benchmark against recent placements and move quickly to land them.
Yes. Data engineers build the pipelines, data scientists and AI engineers build and ship the models, and data analysts turn data into decisions. We match to the exact profile rather than a generic data hire.
For permanent hires it's success-based: you pay only when a candidate starts, with no upfront fee or retainer. Contract placements run on a transparent hourly rate that already covers payroll, compliance, and onboarding. There's no cost to simply engage us.
Still have a question? Talk to a recruiter
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Build your data & AI team with confidence.
Tell us what you’re hiring for and we’ll reply within one business day with a calibrated shortlist, screened for your stack and your team.
- Pay only when they start
- First candidates in 24–48 hrs
- 90-day placement guarantee