Clinical Business Intelligence Manager

Toronto, Ontario, Canada
Remote
Posted Oct 29, 2026
1 position

US$40–US$80 / hour

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Employment type: Contract
Experience level: Senior · 5+ years
Posting language: English
Working hours: 40 hours per week
Location requirements: Country, Toronto, Ontario, Canada
Seniority: Mid-Senior level

Job summary

Lead and mentor a BI team in building and maintaining dashboards, data models, SQL queries, and reporting pipelines for clinical and operational decision-making. Analyze healthcare data, uphold quality and compliance standards, and collaborate with cross-functional teams on AI training projects.

Job details

Clinical Business Intelligence Manager (AI Training) About The Role What if your expertise in healthcare analytics could directly shape how AI understands clinical data — and ultimately influence decisions that affect patient outcomes at scale? We're looking for an experienced Clinical Business Intelligence Manager to lead analytics design and delivery at the intersection of healthcare and cutting-edge AI. You'll guide BI teams in transforming complex clinical, operational, and performance data into trusted dashboards, reports, and insights — and your work will feed directly into AI systems being built and trained by the world's leading research labs. This is a fully remote, flexible contract role designed for a seasoned healthcare analytics professional who wants meaningful work on their own terms. Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week What You'll Do Lead and mentor a business intelligence team in designing and delivering dashboards, reports, and analytics that support clinical and operational decision-making Maintain and optimize BI infrastructure — including data models, SQL queries, and reporting pipelines — ensuring accuracy, reliability, and performance at scale Analyze clinical, operational, and performance datasets to surface actionable trends that support leadership decisions and improve care delivery Translate complex healthcare data into clear, compelling insights accessible to both technical and non-technical stakeholders Ensure data quality, governance, and compliance standards are upheld across all BI outputs in regulated healthcare environments Collaborate asynchronously with cross-functional teams on AI training projects that demand rigorous clinical data expertise Who You Are Proven experience in healthcare or clinical analytics, business intelligence, or data management — you know how clinical data works in the real world Strong track record designing and managing BI systems: dashboards, reporting pipelines, data models, and the infrastructure that supports them Comfortable working with clinical, operational, and administrative datasets in regulated healthcare settings A natural leader — you can guide a team, set quality standards, and mentor others toward better analytical outcomes Detail-oriented and systematic, with a commitment to data accuracy and trusted reporting Self-directed and effective in asynchronous, remote work environments Nice to Have Prior experience with data annotation, data quality assurance, or AI evaluation systems Familiarity with how large language models (LLMs) are trained or evaluated Background working with EMR/EHR systems or population health platforms Experience bridging clinical and technical teams in a leadership capacity Why Join Us Work on cutting-edge AI projects alongside the world's leading research labs Fully remote and flexible — structure your hours around your life, not the other way around Freelance autonomy with the substance of genuinely impactful, senior-level work Direct exposure to how advanced AI models are built and trained using real-world healthcare data Potential for ongoing engagement and contract extension as projects evolve

What you’ll do

Requirements

Candidates should have substantial experience in healthcare or clinical analytics, business intelligence, or data management, including designing and managing BI systems and working with regulated healthcare datasets. They should be effective leaders and mentors, detail-oriented, and comfortable working independently in a remote, asynchronous environment.