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TobogganLabs

Delivers dedicated healthcare engineering and design

Healthcare Data Analyst

Data ScienceConfirmed live in the last 24 hours
Full-timeMontreal, QC, CanadaNo salary listed

About the Job

Requirements

  • Have at least 3 years of professional experience.
  • Have strong hands-on experience with SQL and Python for data analysis and maintain rigorous data quality.
  • Understand economic evaluation, including return on investment, cost-benefit, cost-effectiveness, or budget impact analysis, and be able to defend the assumptions behind a business case.
  • Have exposure to statistical analysis and machine learning.
  • Understand software development best practices and version control systems such as Git.
  • Be familiar with distributed computing and big data technologies.
  • Communicate clearly with non-technical audiences and quickly learn a new client's domain, data model, and vocabulary.
  • Have an academic or professional background in health economics, health outcomes research, the insurance industry, or another quantitative discipline.

Responsibilities

  • Prepare health datasets by validating, cleaning, and structuring claims data, clinical operations data, or application and device data to support reporting and forecasting analyses.
  • Build tested data pipelines and analyses in SQL and/or Python with data engineers to identify trends and insights in data.
  • Develop and maintain complex models to support client decision-making and strategic initiatives, including feature engineering, training, optimization, and performance evaluation of statistical and machine learning models.
  • Quantify the value of the company's work by designing and running return-on-investment, cost-benefit, and budget impact analyses that connect model performance to clients' financial, operational, and clinical outcomes.
  • Provide strategic recommendations based on economic and healthcare policy insights to improve business performance.
  • Communicate with clients by translating business requirements into technical solutions, presenting results and models to non-technical stakeholders, and contributing to status updates and requirements-clarification sessions.
  • Produce reports, dashboards, and documentation that make performance understandable to teammates and clients and keep work reproducible, traceable, and easy to hand over.

Desired Qualifications

  • Have experience with U.S. healthcare data, including claims, remittance, or enrolment files, and code sets such as ICD-10 and CPT/HCPCS.
  • Have measured the value of AI, automation, or digital health interventions by linking model or workflow performance to dollars saved, revenue protected, or improved outcomes.
  • Know the CMS quality-measurement landscape or have exposure to other regulated health domains such as clinical workflows, electronic health record data, or medical devices.
  • Have applied statistical modeling, forecasting, or machine learning techniques beyond descriptive analysis.
  • Have experience with analytics engineering, including testing frameworks such as pytest, data pipeline tools such as dbt or Airflow, continuous integration, or cloud data warehouses.
  • Have prior experience in client-facing roles such as consulting or product/project management.
  • Additional experience in software development and architecture is strongly valued.

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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