Senior Manager, Data Analytics
The Athletic
Lead Growth Product Insights at The Athletic, a sports media company. Manage analysts and use experimentation to inform subscription and product decisions.
Open
Qventus, Inc. develops AI-powered SaaS solutions for hospitals and health systems, helping healthcare teams manage clinical operations and patient flow. Its platform brings together artificial intelligence, machine learning, and behavioral science to automate workflows in perioperative care, pre-admission testing, and inpatient capacity management. By integrating with electronic health records, Qventus delivers operational assistants that handle routine tasks, helping reduce surgery cancellations, support shorter hospital stays, and give clinical staff more time for patient care.
Senior Data Scientist – Healthcare AI (Canada Remote)
Develop production machine learning and LLM systems that improve healthcare operations and patient outcomes. Lead modeling, experimentation, analytics, and data pipeline work in collaboration with clinical, engineering, and product teams.
Description
- Build and maintain large-scale statistical and machine learning models, including NLP and explainable AI methods
- Develop, optimize, and deploy LLM applications with thorough assessments of performance and user trust
- Create experiments and analytics that measure the overall impact of AI in healthcare environments
- Clean and transform datasets while developing SQL and Python data pipelines
- Partner with clinicians, data scientists, platform engineers, and product specialists to turn insights into deployed products
- Present technical findings effectively to both technical and non-technical audiences
- Assess modeling methods and help productionize algorithms with data science and product teams
Requirements
- At least three years of relevant industry experience developing, launching, and maintaining production ML systems at scale
- At least one year of experience developing and optimizing LLM systems
- Proven ability to communicate across technical and non-technical functions
- Practical data engineering experience with dataset manipulation, data cleaning, and Python and SQL pipelines
- Strong software development fundamentals, with a focus on code quality and reliable architecture
- Employment is conditional on successfully completing a pre-employment background investigation and drug test
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