Statistical Analyst

Staff - Non Union

Job Category
M&P - AAPS

Job Profile
AAPS Hourly - Statistical Analysis, Level B

Job Title
Statistical Analyst

Department
Henderson Laboratory | Centre for Disease Control | Faculty of Medicine

Compensation Range
$48.69 - $75.92 CAD Hourly

The Compensation Range is the span between the minimum and maximum base salary for a position. The midpoint of the range is approximately halfway between the minimum and the maximum and represents an employee that possesses full job knowledge, qualifications and experience for the position. In the normal course, employees will be hired, transferred or promoted between the minimum and midpoint of the salary range for a job.

Posting End Date
February 9, 2024

Note: Applications will be accepted until 11:59 PM on the day prior to the Posting End Date above.

Job End Date

Nov 30, 2024

This position is expected to be filled by promotion/reassignment and is included here to inform you of its vacancy at the University.

At UBC, we believe that attracting and sustaining a diverse workforce is key to the successful pursuit of excellence in research, innovation, and learning for all faculty, staff and students. Our commitment to employment equity helps achieve inclusion and fairness, brings rich diversity to UBC as a workplace, and creates the necessary conditions for a rewarding career. 

Job Summary
The primary responsibility of the Statistical Analyst is to lead a Health Canada funded project to generate a multi-year machine learning model of daily wildfire smoke exposures for all of Canada. Project-related responsibilities include: gathering a large volume of relevant data from a wide range of sources at the daily scale; managing and cleaning data for input to the analyses using best practices and GitHub repositories; using sophisticated machine learning methods to train and validate wildfire smoke models at the local, regional, provincial, and national scales; documenting methods and results; generating files with daily estimates for the 2003-2019 period for inclusion in the CANUE data holdings; leading authorship of publications for peer review; establishing automatic systems to operationalize the final model. Additional responsibilities include: liaising with potential data users to ensure they are aware of the new resource; generating results specific to British Columbia for research and surveillance purposes; participating in related epidemiologic studies; and routine reporting to project funders.
Organizational Status
The Statistical Analyst will report directly to the Principal Investigator and interact and liaise with additional co-investigators, project partners, and Knowledge users.
Work Performed
-Designing multiple machine learning methods to model daily wildfire smoke exposure across Canada for the 2003-2019 study period.
-Applying and validating the models at the national scale to assess the most appropriate approaches.
-Developing data pipelines for reproducible acquisition and standardization of multiple remote sensing products at the national scale on a daily basis, resulting in tens of thousands of large files.
-Blending machine learning models with output from deterministic models to evaluate their utility for improving smoke forecasts.
-Documenting methods and procedures in code via GitHub.
-Producing final results to made publicly available for other researchers through the Canadian Urban Environmental Health Research Consortium (CANUE).
-Preparing manuscripts as the lead author.
-Providing expert consultation on machine learning for other lab members interested in using these cutting-edge methods.
-Working collaboratively with others to support project objectives by actively participating at team meetings, and establishing effective communications with project staff and co-investigators
Consequence of Error/Judgement
The Statistical Analyst is required to conduct all activities in an ethical manner. Any procedures or data recorded must be accurate and must accurately reflect the work performed. All activities are accountable to the PI. As data from this effort will be made widely available to a range of data users for surveillance, epidemiological, and policy research, consequences of error could result in erroneous information with negative implications for all of these activities.
Supervision Received
The PI will provide direction and will oversee performance and results of the project. The Statistical Analyst will be expected to develop a work plan and timelines and exercise a considerable amount of judgement and initiative in duties.
Supervision Given
The Statistical Analyst may occasionally supervise and provide direction to other staff or graduate trainees.
Minimum Qualifications
Post-graduate degree in Statistics. Minimum of three years of related experience in research analysis, or the equivalent combination of education and experience.
- Willingness to respect diverse perspectives, including perspectives in conflict with one’s own

- Demonstrates a commitment to enhancing one’s own awareness, knowledge, and skills related to equity, diversity, and inclusion

Preferred Qualifications

A graduate degree in statistics, biostatistics, bioinformatics, or computer science is preferred. Experience with acquisition and management of very large and complex datasets is preferred. Applied experience with machine learning methods and validation approaches is preferred. Familiarity with complex health data and/or remote sensing data is preferred. Related experience in a public health will be an asset. Previous experience with academic publishing will also be an asset. Ability to work effectively with limited oversight. Ability to prioritize and manage work under pressure to meet deadlines. Ability to manage multiple tasks and priorities. Ability to approach others in the machine learning field for information and assistance when necessary. Ability to communicate effectively verbally and in writing. Ability to deal with a diversity of people in a calm, courteous, and effective manner. Ability to maintain accuracy and attention to detail.