Machine Learning Specialist, LaussenLabs (Heart Centre)

at  SickKids

ABOUT SICKKIDS

Dedicated exclusively to children and their families, The Hospital for Sick Children (SickKids) is one of the largest and most respected paediatric healthcare centres in the world. As innovators in child health, we lead and partner to improve the health of children through the integration of healthcare, leading-edge research and education. Our reputation would not have been built – nor could it be maintained – without the skills, knowledge and experience of the extraordinary people who come to work here every day. SickKids is committed to ongoing learning and development, and features a caring and supportive work environment that combines exceptionally high standards of practice.
When you join SickKids, you become part of our community. We share a commitment and determination to fulfill our vision of Healthier Children. A Better World.
Don’t miss out on the opportunity to work alongside the world’s best in paediatric healthcare.

POSITION DESCRIPTION

SickKids is the home of one of the largest physiological waveform datasets (time-series data) in the world, around which we have built a leading data science program. We harness this data with AtriumDB, an end-to-end data science platform built at SickKids to enable rapid ML model development and deployment. We are looking for a Machine Learning specialist (data scientist) to join our leading to push the boundaries on what is possible with this real-time data source. This program is already changing the care we provide to our patients, and we are looking for someone who is eager to make a difference and see the impact their work will create.
Working as part of the LaussenLabs group, the candidate will be supported by a team of other data scientists, ML engineers, software engineers and clinicians. The candidate will apply existing and innovate new techniques in machine learning to solve a variety clinical challenges. Being based in a clinical environment, there will be an opportunity to see the solutions that are developed leveraged at the point of care and become part of an extended clinical team.

• Train, develop, and validate machine learning algorithms on hospital data
• Build end-to-end data pipelines for machine learning models with strong quality control checks and bias assessment
• Rapidly prototype models for exploratory analysis and assess project viability
• Generate and test working hypotheses
• Work at the point-of-care
• Own and manage knowledge sharing within a community
• Mentor and train other junior data scientists and machine learning specialists
• Develop and support training and development opportunities for SickKids staff who want more opportunities to use machine learning