Data Science Specialist

Job Posting #896677

Position: Data Science/Bioinformatics Specialist
Site: Princess Margaret Cancer Centre
Department: Cancer Digital Intelligence
Reports to: Principal Investigator
Salary range: $80,418 - $100,523 per annum (Commensurate with experience and consistent with UHN Compensation Policy)
Hours: 37.5 hours per week
Status: Permanent Full-time

University Health Network (UHN) is looking for an experienced professional to fill the key role of Data Science/Bioinformatics Specialistin our Cancer Digital Intelligence Department.

Transforming lives and communities through excellence in care, discovery and learning.

The University Health Network, where “above all else the needs of patients come first”, encompasses Toronto Rehabilitation Institute, Toronto General Hospital, Toronto Western Hospital, Princess Margaret Cancer Centre and the Michener Institute of Education at UHN. The breadth of research, the complexity of the cases treated, and the magnitude of its educational enterprise has made UHN a national and international resource for patient care, research and education. With a long tradition of groundbreaking firsts and a purpose of “Transforming lives and communities through excellence in care, discovery and learning”, the University Health Network (UHN), Canada’s largest research teaching hospital, brings together over 16,000 employees, more than 1,600 physicians, 8,000+ students, and many volunteers. UHN is a caring, creative place where amazing people are amazing the world.

University Health Network (UHN) is a research hospital affiliated with the University of Toronto and a member of the Toronto Academic Health Science Network. The scope of research and complexity of cases at UHN have made it a national and international source for discovery, education and patient care. Research across UHN’s seven research institutes spans the full spectrum of diseases and disciplines, including cancer, cardiovascular sciences, transplantation, neural and sensory sciences, musculoskeletal health, rehabilitation sciences, and community and population health. Find out about our purpose, values and principles here.

The Cancer Digital Intelligence (CDI) program’s focus is to accelerate the application of discoveries in cancer care through the fusion of human wisdom, data and technology. CDI is one of the strategic pillars of the Princess Margaret Cancer Centre outlined in their 2030 vision, alongside Early Detection, Beyond Chemotherapy, and Comfort and Confidence.
At CDI, we develop the infrastructure and solutions needed to harness the profusion of health information for innovative care solutions. Our data-driven solutions span three primary Innovations areas, all of which are supported by our Data Science and Analytics core: Care Innovation, Business Intelligence, and Discovery Integration.

This role is specifically within the foundational Data Science and Analytics core and involves building deep expertise to advance novel applications of data visualization, digital platforms, and highly-contextualized applications of artificial intelligence and machine learning methods. The team works in close collaboration with care providers, researchers, and educators to develop innovative solutions that collect, manage, and leverage data to facilitate clinical research and translational care practices. Our systems are used in clinical practice and in multi-site research studies.

Key success factors for this role:

• Curious and independent approach to the exploration, visualization, modeling and predictive modeling of cancer care data (clinical, demographic, imaging, genomic, etc.).
• Participation, development, and consultancy of streamlined computational analysis pipelines and ML/AI solutions.

As a Data Science Specialist, you will be responsible for designing, coding, implementing, and presenting ML/AI solutions pertaining to a variety of different data types. You will actively solve novel problems, build predictive models, make improvements, and troubleshoot independently and with your team.
This role requires experience in using a range of different data types, statistical techniques, and ML/AI methodologies to answer innovative healthcare questions. You will work on novel research questions and translational healthcare technologies to facilitate the acceleration of cancer research, identification of clinically important biomarkers, and understanding of patient populations.

This role requires a unique combination of skills that are needed to complete the ML development cycle (research and data mining, model development and validation, and implementation). You will have the option to work remotely, on-site, or hybrid, with flex-hours.

Responsibilities:

Individual responsibilities

• Apply expert knowledge of computational analysis in areas such as patient-centric-omics data, and data integration to enable progression of innovative biomarkers and ML models into the clinic
• Develop quality control and data processing tools for a broad range of digital and clinical data types
• Leverage patient data to enable hypothesis generation and design studies for validation in clinically relevant contexts
• Identify issues of practical or theoretical importance and then conduct independent studies to derive solutions through innovative mathematical/computational approaches
• Iterate on key features and build new statistical and machine learning models relating measured features to clinical endpoints
• Perform statistical analysis on patient datasets including parametric and non-parametric tests, data mining and ML/AI algorithms
• Collaborate with clinical care providers, researchers and educators to understand pertinent research questions and facilitate data-driven program decisions
• Interpret and communicate technical results and methods clearly and interact cross-functionally with a wide variety of people and teams
• Be well informed about current trends in ML and AI.

Team responsibilities

• Work openly and collaboratively with all pillars of the PM Cancer Digital Intelligence Program
• Self-Motivate and set high standards of performance while driving for results and achievements
• Share knowledge with enthusiasm and empower your colleagues
• Show respect and appreciation for your colleagues’ needs and appreciate differences as much similarities
• Work on multiple concurrent projects and products, effectively following timelines, goals, and cross-functional collaborations
• Take responsibility for your personal and professional development
• Lead and provide supervision to personnel when required.

Qualifications:

• PhD degree in machine learning, computer science, bioinformatics, statistics, applied mathematics or related disciplines, or masters degree in similar fields with six (6) + years of experience
• Excellent communication skills and ability to utilize a collaborative approach to solving challenging problems
• Experience with Python (scikit-learn, Pandas, etc.) and deep learning frameworks (TensorFlow or PyTorch)
• Experience with healthcare data types, topics, and scientific challenges and approaches.

Vaccines (COVID and others) are a requirement of the job unless you have an exemption on a medical ground pursuant to the Ontario Human Rights Code.

If you are interested in making your contribution at UHN, please apply on-line. You will be asked to copy and paste as well as attach your resume and covering letter. You will also be required to complete some initial screening questions.

Posting Date: April 7, 2022 Closing Date: Until Filled

For current UHN employees, only those who have successfully completed their probationary period, have a good employee record along with satisfactory attendance in accordance with UHN’s attendance management program, and possess all the required experience and qualifications should apply.

UHN thanks all applicants, however, only those selected for an interview will be contacted.

UHN is a respectful, caring, and inclusive workplace. We are committed to championing accessibility, diversity and equal opportunity and welcomes all applicants including but not limited to: all religions and ethnicities, LGBTQ2s+, BIPOC, persons with disabilities and all others who may contribute to the further diversification of ideas. Requests for accommodation can be made at any stage of the recruitment process providing the applicant has met the Bona-fide requirements for the open position. Applicants need to make their requirements known when contacted.