Data Scientist - Vancouver, Canada - University of British Columbia
Description
Staff - Non UnionJob Category
M&P - AAPS
Job Profile
AAPS Salaried - Statistical Analysis, Level A
Job Title
Data Scientist (NLP)
Department
Research | Data Science Institute | Faculty of Science
Compensation Range
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 DateMarch 4, 2024
Note:
Applications will be accepted until 11:59 PM on the day prior to the Posting End Date above.
Job End Date
Apr 30, 2025
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 University of British Columbia Data Science Institute (DSI) is seeking a Data Scientist (NLP) to join our research team.
Specifically, we are seeking an outstanding individual with experience and interest in Natural Language Processing (NLP) and Machine Learning (ML).
As a key member of our research team, the Data Scientist (NLP) will build cutting-edge data platforms and conduct interdisciplinary research at the intersection of data science, machine learning and public health.
The research program collaborates with local health organizations and may involve activities at healthcare facilities and premises; therefore, this position must adhere to applicable Provincial Health Orders.
The Data Scientist (NLP) will also work closely with a diverse team of data scientists, postdoctoral fellows, domain experts, and students.
Organizational Status
Work Performed- Design, develop, implement and evaluate methods, pipelines and tools for the analysis of text and quantitative data sets, which may include, but not limited to, tools for information extraction, sentiment analysis and topic modelling- Design, develop, implement and evaluate machine learning methods for building predictive models- Manage research projects and ensure all stakeholders are kept up-to-date on progress and outcomes- Communicate research goals and results to both technical and non-technical audiences- Work effectively in an interdisciplinary environment by engaging a team of clinicians and researchers from health, computer science and statistics, etc.
Consequence of Error/Judgement
The incumbent is given wide latitude for exercising independent initiative and judgment in performing specialized duties and responsibilities. A lack of judgment could harm the DSI and partner organizations' research and funding.
The incumbent will interact with multiple researchers across various organizations to address their data needs and research findings, and discretion is vital.
Supervision Received
The incumbent will be able to work independently with mínimal supervision and regularly report to the DSI Senior Data Scientist.
The incumbent will also receive support and guidance from the DSI Scientific Director and research collaborators as needed to familiarize themselves with the health systems.
Supervision Given
The incumbent will assist the DSI Scientific Director and DSI Senior Data Scientists with the supervision and mentoring of junior research trainees (e.g., co-op students).
Post-graduate degree in Statistics. Minimum of two 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- M.Sc. from a qualitative research field; e.g., computer science, statistics, applied mathematics, data science; or a minimum of two years of experience in research analysis or equivalent education and experience
Knowledge and Experience- Excellent programming experience e.g., Python, R, Java, JavaScript, C#, C++- Excellent knowledge and experience in Natural Language Processing.
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