Data Scientist, BC Cancer

Job ID 2434342_pl355 Date posted 06/18/2025 Job Summary:

In accordance with the Mission, Vision and Values, and strategic directions of Provincial Health Services Authority (PHSA) patient safety is a priority and a responsibility shared by everyone at PHSA, and as such, the requirement to continuously improve quality and safety is inherent in all aspects of this position.
The Data Scientist acts in accordance with the cognitive computing priorities of BC Cancer to build and increase capacity and support for our cognitive computing learning systems to create and enhance insights gained from analyzing quality data. The Data Scientist is adept at using large data sets and machine learning models to find opportunities for product and process optimization as well as to test the effectiveness of different courses of action. They use a variety of data mining / data analysis techniques, and utilize their knowledge of the full AI product lifecycle of development, testing, implementation, and maintenance. The Data Scientist will drive business results with their data-based insights and works with a wide range of stakeholders and functional teams. The Data Scientist will discover solutions hidden in large data sets and work with stakeholders to improve business processes and outcomes.

Duties/Accountabilities:

• Work as the lead data scientist and strategist for Quality and Patient Safety, to foster and develop a solid and sustainable machine learning foundation and competency for BC Cancer
• Work closely with clinical and leadership teams across the health authority to strategize, develop, and implement AI products
• Identify, clean, and integrate large sets of structured and unstructured datasets from disparate sources for use in ML models and products
• Use advanced ML processes to convert data from non-functional forms, such as scanned image text, to functional forms ready for use in further ML models
• Use advanced ML models to identify patterns, trends, and opportunities that can make predictions or reduce workload to make a significant impact across various domains within BC Cancer
• Lead the process of implementation of ML models into production by collaborating with developers and other stakeholders.
• Communicate analytic solutions to leadership and apprise leadership of AI product status throughout the various stages of the product lifecycle
• Implement improvements as needed to already implemented AI products

Qualifications:

A level of education, training, and experience equivalent to a Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field, 5-7 years of experience working with large datasets and machine learning models.
Advanced skills in AI product design and the analysis of quantitative data for the purpose of creating actionable insights and measureable impact. Thorough knowledge of the principles, processes, procedures and methods involved in data analysis, statistical methods, and machine learning. Demonstrated expertise in planning, organizing and coordinating AI product activities. Demonstrated proficiency with using advanced machine learning methods, machine learning software packages, and manipulation of large datasets. Knowledge and experience in statistical and data mining techniques including but not limited to: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, simulation, scenario analysis, clustering analysis, decision trees, neural networks, etc. Experience writing computer code, querying databases, and using statistical computer languages: Python, SLQ, R, etc. Experience using web services: Redshift, S3, Spark, DigitalOcean, etc. Experience with distributed data/computing tools: Map/Reduce, Hadoop, AWS, Hive, Spark, Gurobi, MySQL, etc. Experience visualizing/presenting data for stakeholders using: Jupyter, Matplotlib, D3, ggplot, Periscope, Business Objects, etc. Demonstrated expertise in knowledge synthesis and translation activities. Demonstrated ability to communicate effectively, both verbally and in writing. Ability to work collaboratively in an interdisciplinary environment.