Lead Data Scientist- Canada

Lead Data Scientist

(Remote – Canada)
About Very

Very is a fully distributed technology firm led by expert problem-solvers who create efficient, scalable solutions that move commercial, industrial, and consumer products from pilot to production in record time.

We believe that real innovation happens in the grind, working shoulder to shoulder with clients who are building the future. Our team thrives on that energy. When we're not helping clients deliver business-critical outcomes, we're refining our craft and celebrating what it means to do hard things well.

We've built a collaborative, tight-knit culture that thrives in both remote and in-person settings. We've won numerous workplace awards over the years, including Great Place to Work certification and recognition from Parity.org as a Best Company for Women to Advance.

Our clients include well-known brands like Vizio, Peloton, Clear, iHeart Radio, and Fellowes, all determined to leverage connected devices and AI to drive meaningful impact. Our job is simple: help them win.
About This Role

A Lead at Very is an individual who operates with the highest degree of knowledge and accountability for the delivery of services to our customers. They provide excellent technical leadership and delivery skills, as it pertains to complex, multi-faceted projects at Very. They have a strong executive presence, which gives major client stakeholders the confidence that we will deliver, and gives our team the confidence and accountability to do so.

As a Lead Data Scientist at Very, you own the data and modeling workstream on client engagements. You will be handed a vague client outcome and a small budget, and expected to independently decide the architecture, the evaluation design, and what to tell the client. You make architecture calls, defend them internally, present results directly to non-technical owners, and recognize when the highest-leverage next step is a change to the data or approach rather than further tuning.

The work is roughly 30 percent modeling, 30 percent data and infrastructure plumbing, and 40 percent client-facing judgment. This is not a research role. The people who succeed here are as comfortable owning a data pipeline end to end as they are training a model.

Lead engineers also serve as solutions engineers for the commercial team, helping close contracts with terms that are conducive to successful delivery.

This is not an easy role. You'll work in complex domains, under real deadlines, and with clients who expect you to bring clarity, confidence, and results. If you find satisfaction in doing hard things well, in solving tough problems, building real systems, and helping others rise to the challenge, you'll fit right in.

As a client services organization, travel may be required up to 10% of the time.
What You'll Be Working On

Almost all of our projects are production systems. Recent engagements have included two representative shapes of work:

Applied computer vision on physical-world measurement problems. Turning raw video into labeled training datasets, training and evaluating vision models against noisy real-world ground truth, standing up cost-aware hosted inference for large models, and translating error metrics into plain business language for a client who thinks in dollars, not RMSE.

Agentic data platforms. Ingesting unreliable public or client data into a well-designed relational schema, building hybrid lexical and semantic retrieval, exposing typed tool interfaces to LLMs, and defending the correctness of every answer to technically curious stakeholders who test the system adversarially.

These two shapes are representative, not exhaustive; the exact nature of your projects will vary. Across our engagements, we typically leverage the following:

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Core: Python at a production engineering level, PyTorch, the SciPy stack, Git and GitHub Actions, agentic AI development (MCP servers, LLM APIs, typed tool design)

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Data and backend: PostgreS