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Location:
Montreal, Canada ? Employment: Full-time ? Work model: On-site, 5 days a week ?

Salary:
CA$100,000 – CA$140,000 per year ? Work authorisation: Applicants must already have the right to work in Canada. Visa sponsorship is not available. We're hiring for a health-tech Series A startup that lets people track their hormones continuously instead of relying on occasional lab tests. You'll join the ML team as an Applied Scientist , reporting to the ML lead who built Eli's current system. The work is scientific problem solving on imperfect, noisy real-world data, not ML infrastructure; the ML lead supports integration and productionization. Two data sources: the app's analysis of each test result (the color read by the ML engine), and the daily series of results that builds each user's curve. You will own:
- Explore datasets and understand the underlying data-generating processes.
- Develop, evaluate and improve machine learning, signal processing and statistical models.
- Run feature engineering, model selection, validation and error analysis.
- Identify confounding, data leakage, measurement variability and distribution shift.
- Design experiments and analyses to resolve uncertainty and guide modelling decisions.
- Investigate new approaches, from classical ML to deep learning where appropriate.
- Write clear, reproducible Python code (beyond notebooks) and communicate findings to technical and non-technical stakeholders.
- Build analyses and models with production deployment in mind.




- Investigate model performance and failures using real production data.
- Run ongoing error analysis, diagnostics and root-cause investigations.
- Spot distribution shifts, edge cases, systematic biases and performance degradation.
- Turn production observations into experiments, improvements or data-collection strategies What we're looking for ?
- Bachelor’s degree in Engineering, Computer Science, Data Science, Mathematics or a related field. Master’s or PhD preferred.
- Minimum 5 years of professional experience, excluding internships.
- Strong foundation in machine learning fundamentals, statistics and experimental reasoning.
- Strong Python and experience with common ML and data science libraries.
- Able to work independently on ambiguous problems and decide which questions need answering.
- Positive grasp of model validation, uncertainty, bias/variance and generalisation.
- Able to tell a statistically or scientifically meaningful improvement from one that only moves a metric. Why join?
- Be part of the core team developing and commercialising the first product to monitor hormonal data daily and over a lifetime.
- Join at an early stage, in a small (under 25), high-performing and diverse team where your work shapes the company’s direction.
- Autonomy: people drive their own work and solve open-ended problems proactively.
- Health insurance (medical, dental, vision and more), plus flexibility over schedule and vacations.
- Office and R&D; facilities in Montreal, with a distributed team that favours asynchronous work and fewer meetings

📌 Applied Scientist (Montreal)
🏢 Key Talent Solutions
📍 Montreal