Data Science Specialist

Found in: beBee jobs CA - 1 week ago

Toronto, Ontario, Canada University Health Network Full time

Data Science Specialist

Job Posting #: 929405

Union: Non-Union

Site: Toronto General Hospital

Department: AI Hub

Reports to: Principal Investigator

Hours: 37.5 hours per week

Salary: $43.11 to $53.89 hourly. To commensurate with experience and consistent with UHN compensation policy

Status: Temporary Full Time (1 year)

Shifts: Day

Posted Date: March 7, 2024

Closing Date: April 6, 2024

The University Health Network, where "above all else the needs of patients come first", encompasses Toronto General Hospital, Toronto Western Hospital, Princess Margaret Cancer Centre, Toronto Rehabilitation Institute and the Michener Institute of Education. 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 ground breaking 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 1,200 physicians, 8,000+ students, and many volunteers. UHN is a caring, creative place where amazing people are amazing the world.

Position Summary

We are looking for a Data Science Specialist with health care and machine learning experience to join our University Health Network (UHN) Collaborative Centre for Artificial Intelligence (AI) and Data Science to work with the cancer program. The UHN AI Hub brings together scientists and clinicians from across UHN working to develop and implement safe and responsible applications of AI to improve health care. This role involves working in close collaboration with care providers, researchers and students to build deep expertise and advance novel applications of artificial intelligence and machine learning (ML) methods to facilitate research and translation into clinical practice.

The Data Science Specialist will design and develop highly sophisticated ML software solutions, platforms and methodologies to support high priority initiatives with cutting edge AI technology within the UHN network. The Data Science Specialist works closely with the Chief AI Scientist and team to apply AI methods to solve complex health related questions, improve hospital efficiency and develop new research hypotheses. Primary responsibilities include, but are not limited to, working with large datasets, preprocessing, cleaning and organizing data for analysis, developing and implement NLP models, performing quality assurance testing, support and maintenance of new and existing applications. The Data Science Specialist will collaborate with oncology clinicians and scientists to analyze and interpret various data modalities such as imaging, clinical medical record data, signal processing and genomic data. The Data Science Specialist will possess strong technical proficiency, creativity, and strong collaborative skills to contribute towards furthering AI capacity and innovation within UHN.

Duties

Data Processing and Analysis: Working with large datasets of oncology data. This involves preprocessing, cleaning, and organizing data for analysis as well as systematic exploration of high-dimensional data to identify new computational approaches and Integrative analysis of multiple data types. Model Development and Implementation: Develop and implement NLP models to extract insights from biological data. This could include text mining from scientific literature to identify current trends and the latest discoveries. Interpret and communicate technical results and methods clearly and interact cross-functionally with a wide variety of people and teams. Algorithm Optimization: Fine-tune algorithms for specific tasks, like sequence alignment, gene expression pattern recognition, and variant calling. Collaborative Research: Work closely with biologists and clinicians to understand their data needs and translate these into computational tasks. Publishing and Documentation: Regularly document your findings and methodologies. Publish in peer-reviewed journals and present at conferences. Grant Writing: Assist in writing grant proposals for funding research projects. Mentoring and Supervision: Guide junior researchers or students in their projects, providing expertise in oncology data analysis.

Qualifications

Master's Degree required, PhD would be an asset, in machine learning, computer science, bioinformatics, statistics, applied mathematics or related disciplines. Minimum 6 years related experience required. Excellent communication skills and ability to utilize a collaborative approach to solving challenging problems. Experience with developing and implementing ML and NLP models.

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