Data Scientist, Data, Analytics, Evaluation and Re...

Job description

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. As such, the requirement to continuously improve quality and safety is inherent in all aspects of this position.
Reporting to a Director, Data Analytics Reporting and Evaluation (DARE), the Data Scientist develops, operationalizes and improves analytical models to support and inform operational, tactical and strategic decision making at PHSA. The Data Scientist is adept at using large data sets to build Operations Research models to find opportunities for service delivery and process optimization, as well as to test the effectiveness of different courses of action. Employs a variety of modeling and data analysis techniques, and utilizes knowledge of the operations and care delivery to build realistic models. The Data Scientist drives business results with evidence-based insights and works with a wide range of stakeholders and functional teams. The Data Scientist discovers solutions hidden in large data sets and works with stakeholders to improve business processes and outcomes.

  • Works as a senior data scientist and strategist in DARE to develop improvements to operational workflows and support decision making by researching, developing, and evaluating models and algorithms that leverages tools such as process modeling, operations research, simulation, and optimization and applied machine learning.
  • Works closely with clinical and operational leadership across PHSA and other health authorities to strategize, develop, and implement analytical products.
  • Uses advanced Operations Research and Machine Learning models to identify patterns, trends, and opportunities that can make predictions or reduce workload and increase system efficiency to make a significant impact across various domains within PHSA.
  • Leads the process of implementation of models into a useful product by collaborating with developers and other stakeholders.
  • Communicates analytic solutions with leadership and apprises leadership of the product status throughout the various stages of the product lifecycle.
A level of education, training, and experience equivalent to a PhD degree in Operations Research, Industrial Engineering, Mathematics, Computer Science or another quantitative field with 5-7 years of experience in related areas. Experience in health care sector would be an asset.
Advanced skills in design of Operations Research models 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, optimization and discrete event simulation methods, and machine learning. Demonstrated expertise in planning, organizing and coordinating modeling projects, and ability translating complex technical concepts to other stockholders to inform their decision making. Demonstrated proficiency with using advanced machine learning methods, optimization and simulation software packages (e.g., CPLEX, GAMS, Arena, Simio, etc.), and manipulation of large datasets. Knowledge and experience in statistical and data mining techniques including but not limited to: regression methods, mathematical modeling, system dynamics, analysis of variance, text mining, simulation, scenario analysis, clustering analysis, decision trees, and neural networks. Experience with programing, querying databases, and using statistical computer languages: Python, SQL, R, SAS and others. Experience visualizing/presenting data for stakeholders using: R, ggplot, Tableau, PowerBI, Matplotlib. Demonstrated ability to communicate effectively, both verbally and in writing. Ability and passion to work collaboratively in an interdisciplinary environment.

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