“Join us for a unique ML Resident role focusing on improving patient outcomes by predicting risk of an adverse event leading to an emergency room visit using ML/DL. You’ll work in a fast-paced and dynamic team of machine learning scientists, healthcare providers, and domain experts.”

• Soumik Farhan, Machine Learning Scientist

REQUIRED SKILLS / EXPERTISE

We’re looking for a talented and enthusiastic individual with solid knowledge of machine learning experience working with health care data, and a passion to improve individual health outcomes.

REQUIRED QUALIFICATIONS:

• Completion of a Computer Science (or a related graduate degree program) MSc. or PhD with specialization in predictive health or medical applications.
• Proficient in developing and training, fine-tuning and evaluating machine learning and deep neural network models in PyTorch and/or TensorFlow.
• Proficient in Python programming language and related ML frameworks, libraries and toolkits.
• Solid understanding of classical statistics and its application in model validation.
• Familiarity with Linux, Git version control, and writing clean code.
• A positive attitude towards learning and understanding a new applied domain .
• Must be legally eligible to work in Canada.

PREFERRED QUALIFICATIONS:

• Familiarity with and hands-on experience with medical and/or health data.
• Publication record in peer-reviewed academic conferences or relevant journals in machine learning.
• Experience/familiarity with software engineering best practices.
• Experience using cloud platforms (GCP, AWS, Azure, etc.)

NON-TECHNICAL REQUIREMENTS:

• Desire to take ownership of a problem and demonstrated leadership skills.
• Interdisciplinary team player enthusiastic about working together to achieve excellence.
• Capable of critical and independent thought.
• Able to communicate technical concepts clearly and advise on the application of machine intelligence.
• Intellectual curiosity and the desire to learn new things, techniques, and technologies.

ABOUT THE ROLE

This is a paid residency that will be undertaken over a twelve-month period with the potential to be hired by our client afterwards. The resident will be reporting to an Amii Machine Learning Scientist and regularly consult with the Client team to share insights and engage in knowledge transfer activities.

KEY RESPONSIBILITIES:

• Utilize a range of supervised, unsupervised methods to build a robust and deployable predictive model.
• Ingest and understand (including performing exploratory data analysis and baseline statistical assessments) medical data from multiple patient health data sources.
• Experiment and fine-tune the model(s) as necessary based on the performance of baseline and deployment expectations.
• Collaborate with the project team and domain experts to iteratively develop models and define identified health event outcomes.
• Implement model explainability and interpretability techniques to provide insights to patients and clinicians.
• Participate in regular meetings with the client and stakeholders, preparing presentations and reports.
• Research and implement different approaches to the problem from literature as well as publicly available tools.