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TobogganLabs

Delivers dedicated healthcare engineering and design

Data Scientist

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeMontreal, QC, CanadaNo salary listed

About the Job

Requirements

  • Have 5 or more years of professional experience.
  • Have experience with Python and cloud computing platforms.
  • Have a solid understanding of machine-learning algorithms, deep learning, and generative AI models.
  • Have experience building and deploying machine-learning pipelines with cloud technologies.
  • Have familiarity with distributed computing and big data technologies.
  • Understand software-development best practices and version-control systems such as Git.
  • Have a master's degree in an AI-related discipline.
  • Have worked in client-facing roles such as consulting.

Responsibilities

  • Design, integrate, train, and optimize machine-learning or generative AI models to meet client needs, including feature engineering and performance evaluation.
  • Explore client data to identify patterns and opportunities; clean and structure data in collaboration with data engineers.
  • Translate business requirements into technical solutions; present results and explain models to non-technical stakeholders.
  • Stay current on machine-learning and AI advances and healthcare-sector regulatory requirements, including HIPAA, Bill 25, and GDPR.
  • Document approaches and results to ensure traceability and facilitate knowledge transfer.

Desired Qualifications

  • Experience in client-facing roles such as consulting or product/project management.
  • Experience working in healthcare or other highly regulated industries.

About the Company

TobogganLabs

Delivers dedicated healthcare engineering and design

Toboggan Labs provides dedicated engineering, design, and data science teams to healthcare clients, acting as extended in-house tech groups to de-risk and accelerate product development. It deploys experienced technologists to handle technology strategy, data science, software engineering, and AI-driven clinical tools for startups and healthcare organizations. The company focuses on healthcare interoperability (FHIR/HL7), clinical workflow automation, and compliant systems (HIPAA and FDA) to modernize legacy platforms and build new digital tools. Its goal is to speed digital transformation in healthcare by supplying ready-to-deploy teams that shorten hiring time, reduce development risk, and deliver end-to-end technology and AI capabilities, including support for transitioning AI research to production through partnerships like Mila.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
Montreal, Canada
Founded
2020

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