Salary range: The salary range for this position is CAD $55.25 - $79.42 / hour Why Fraser Health?:
Are you looking for that opportunity to put your established data expertise to use in healthcare? Do you take responsibility for your own performance and aim to model integrity, resilience and confidence? If you have answered “yes”, we want you to keep reading! We are currently looking for a Full Time Data Scientist to join our Centre for Advanced Analytics, Data Science, and Innovation (CAADSI) team at the Central City office located in Surrey, B.C. with flexible work options.
Position Highlights
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Work as the lead Data Scientist and strategist to foster and develop a solid and sustainable machine learning foundation and competency for Fraser Health.
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Work closely with clinical and leadership teams across the health authority to strategize, develop, and implement artificial intelligence (AI) products.
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Identify, clean, and integrate large sets of structured and unstructured datasets from disparate sources for use in ML models and products. Enhance data collection procedures to include information that is relevant for building advanced ML models.
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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.
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Use advanced ML models to identify patterns, trends, and opportunities that can make predictions or reduce workload to make a significant impact across various clinical domains within Fraser Health
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Lead the process of implementation of ML models into production by collaborating and guiding developers.
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Identify, engage, and collaborate with specific stakeholders as required for the development of AI products
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Communicate analytic solutions to leadership and informs leadership of AI product status throughout the various stages of the product lifecycle.
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Make recommendations to leadership regarding strategic actions to maintain the ML development pipeline, analytic architectures, and life cycle to avoid potential negative consequences and system failures increase positive impact of ML systems.
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Maintain detailed project status plans in order to achieve ML development cycle timelines avoiding development delays
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Assess and implement improvements as needed to already existing AI products and creates anomaly detection systems to track performance and data accuracy.
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Keep up-to-date with latest technology trends and methods.
To join our team, ideally, we are looking for you to have:
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PHD in Statistics, Mathematics, Computer Science or another quantitative field
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Five to seven years of experience working with large datasets and machine learning models
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Experience with Generative AI and Large Language Models is preferred
- An equivalent combination of education, training and experience may be acceptable
If this sounds like the ideal role for you, here are more reasons why you should apply:
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A career with Fraser Health will offer you the opportunity to be a part of a dedicated team of experts in a dynamic and rewarding health care environment.
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We offer a competitive compensation and benefit package, including comprehensive health benefits coverage.
Are you ready to take the next step in your career? Apply today so we can continue the conversation and make a difference in the communities we serve. We value diversity in the work force and aim to maintain an environment of Respect, Caring & Trust.
Detailed Overview:
Supporting the Vision, Values, Purpose and Commitments of Fraser Health including service delivery that is centered around patients/clients/residents and families:
Reporting to the Senior Data Scientist, the Data Scientist acts in accordance with the cognitive computing priorities of Fraser Health to build and increase capacity and support for the cognitive computing learning systems to create and enhance insights gained from analyzing quality data. The Data Scientist adeptly uses large data sets and machine learning (ML) models to find opportunities for product and process optimization as well as to test the effectiveness of different courses of action. Discovers solutions hidden in large data sets and works with stakeholders and functional teams to improve business processes and outcomes.
Responsibilities:
- Works as the lead Data Scientist and strategist for the assigned program, to foster and develop a solid and sustainable machine learning foundation and competency for Fraser Health.
-
Works closely with clinical and leadership teams across the health authority to strategize, develop, and implement artificial intelligence (AI) products.
-
Identify, clean, and integrate large sets of structured and unstructured datasets from disparate sources for use in ML models and products. Enhance data collection procedures to include information that is relevant for building advanced ML models.
-
Uses 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.
-
Uses advanced ML models to identify patterns, trends, and opportunities that can make predictions or reduce workload to make a significant impact across various clinical domains within Fraser Health
-
Leads the process of implementation of ML models into production by collaborating and guiding developers.
-
Identifies, engages, and collaborates with specific stakeholders as required for the development of AI products
-
Communicates analytic solutions to leadership and informs leadership of AI product status throughout the various stages of the product lifecycle.
-
Make recommendations to leadership regarding strategic actions to maintain the ML development pipeline, analytic architectures, and life cycle to avoid potential negative consequences and system failures increase positive impact of ML systems.
-
Maintains detailed project status plans in order to achieve ML development cycle timelines avoiding development delays
-
Assess and implements improvements as needed to already existing AI products and creates anomaly detection systems to track performance and data accuracy.
-
Keeps up-to-date with latest technology trends and methods.
Qualifications:
Education and Experience
PHD in Statistics, Mathematics, Computer Science or another quantitative field, 5-7 years of experience working with large datasets and machine learning models. An equivalent combination of education, training and experience will also be considered.
Competencies
Demonstrates the leadership practices of the Fraser Health Leadership Framework of Clear, Caring and Courageous and creates the conditions for people to succeed.
Professional/Technical Capabilities
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Advanced skills in AI product design and the analysis of quantitative data for the purpose of creating actionable insights and measureable impact.
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Thorough knowledge of the principles, processes, procedures and methods involved in data mining, data analysis, statistical methods, and machine learning.
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Demonstrated expertise in planning, organizing and coordinating AI product activities.
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Demonstrated proficiency with using advanced machine learning methods, machine learning software packages, and manipulation of large datasets.
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Knowledge and experience in statistical and data mining techniques including but not limited to: GLM/Regression, Random Forest, Boosting, Trees, text mining, network analysis, simulation, scenario analysis, clustering analysis, decision trees, neural networks, etc.
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Experience writing computer code, querying databases, and using statistical computer languages: Python, SLQ, R, etc.
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Experience using web services: Redshift, S3, Spark, DigitalOcean, etc.
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Experience with distributed data/computing tools: Map/Reduce, Hadoop, AWS, Hive, Spark, Gurobi, MySQL, etc.
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Experience visualizing/presenting data for stakeholders using: Jupyter, Matplotlib, D3, ggplot, Periscope, Business Objects, etc.
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Demonstrated expertise in knowledge synthesis and translation activities.
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Demonstrated ability to communicate effectively, both verbally and in writing.
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Ability to work collaboratively in an interdisciplinary environment.
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Ability to analyze complex issues and develop recommendations using facilitation and consensus building.
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Demonstrated critical thinking and analytical skills including statistical analysis and evaluation methodology.
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Ability to prepare and present information to multiple audiences.
