Data scientist
1 month ago
Full time
1 day ago, from Provincial Health Services Authority
In accordance with the Purpose, Vision, Values and Coast Salish Teachings, and strategic directions of PHSA, safety, including both patient and employee 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.
The Provincial Health Services Authority (PHSA) plans, manages and evaluates selected specialty and province-wide health care services across BC, working with the five geographic health authorities to deliver province-wide solutions that improve the health of British Columbians. PHSA embodies values that reflect a commitment to excellence.
Reporting to the Director, Data Science and Innovation, the Data Scientist II works under the supervision of a Data Scientist III and acts in accordance with the analytics and computing priorities of the BC Centre for Disease Control. This role aims to support our computing learning systems to create and/or enhance insights gained from analyzing quality data, and to build and increase capacity by automating existing pipelines and processes, and to make recommendations on the restructuring and optimization of service line & department resources. The Data Scientist II is able to use large data sets and machine learning models to find opportunities for product and process optimization, elimination or streamlining of resources, 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 II will support business results with their data-based insights and works with a wide range of parties and functional teams.
Duties/Accountabilities:
- Participates in the design, development, and implementation of all cycles of data science, machine learning, and artificial intelligence model development to support data driven decision-making and improve delivery of care.
- Participates in the process of implementation of machine learning models into a useful product by collaborating with developers, departments, service lines, and other partners, in order to identify opportunities for automation to enable the efficient reallocation of resources.
- Prepares confidential reports regarding opportunities and recommendations for resource allocation and/or distribution.
- Performs inferential or forecasting analyses. Performs diagnostic analysis on model fits and identifies potential issues and model improvements. Uses cross-validation and other approaches to assess model accuracy and predictive performance. Creates reports of resulting forecast diagnostics, performance, and predictions. Assists with writing of results for briefing notes and scientific publications.
- Utilizes advanced statistical techniques for analyzing complex datasets, including longitudinal data analysis. Designs simulation modelling in the context of evaluating public health measures. Employs data preprocessing techniques, feature engineering, and data imputation methods to ensure data quality and model accuracy.
- Identifies, cleans, and integrates large sets of structured and unstructured datasets from disparate sources for use in advanced analytical models and products. Troubleshoots coding problems quickly and efficiently to ensure a productive workplace.
- Uses advanced machine-learning processes to convert data from non-functional forms, such as unstructured text or scanned image text, to functional forms ready for use in further machine learning models.
- Uses advanced machine-learning models to identify patterns, trends, and opportunities that can make predictions or reduce workload to make a significant impact across various domains within BCCDC.
- Communicates analytic solutions to leadership and apprise leadership of AI product status throughout the various stages of the product lifecycle.
- Implement improvements as needed to current AI products.
Qualifications:
A level of education, training, and experience equivalent to a Master’s in Statistics, Mathematics, Computer Science, or another quantitative field, and five (5) years of experience working with large datasets and machine learning models. Demonstrated skills in AI product development and the analysis of quantitative data for the purpose of creating actionable insights and measurable 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 and other regression, Bootstrapping, Random Forests, Boosting, Trees, text mining, social network analysis, simulation, scenario analysis, clustering analysis, decision trees, neural networks, and other methodology. Experience writing computer code, querying databases, and using statistical computer languages: Python, SQL, R, SAS, and others. Experience with distributed data/computing tools, including Hadoop, AWS, Hive, Spark, Gurobi, MySQL, or similar. Experience visualizing/presenting data for stakeholders using: R/RStudio Shiny, Tableau, PowerBI, D3, Periscope/Sisense or other. 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.
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