Data Scientist

3 weeks ago

Vancouver, Canada University of British Columbia Full time

Staff - Non Union

Job Category

M&P - AAPS

Job Profile

AAPS Salaried - Statistical Analysis, Level A

Job Title

Data Scientist (General)-1

Department

Research | Data Science Institute | Faculty of Science

Compensation Range

$6,068.92 - $8,724.25 CAD Monthly

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

June 3, 2024

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

Job End Date

Jul 31, 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 (General) to join our research team. Specifically, we are seeking an outstanding individual with experience and interest in Machine Learning (ML) and/or Natural Language Processing (NLP). As a key member of our research team, the Data Scientist (General) will build cutting-edge data platforms and conduct interdisciplinary research at the intersection of data science, machine learning and various fields within the Faculty of Science, such as biology, chemistry and physics. The Data Scientist (General) 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 diverse data sets, which may include, but not limited to, imaging, time series, text, sequences and high-dimensional datasets- 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 researchers from computer science, statistics, and other Science disciplines- Contribute to curriculum and workshop development in data science- Deliver guest presentations and/or professional workshops on data science topics- Respect privacy and ethics around the use of sensitive and privileged data sets- Work effectively in a team environment with limited supervision- Respect and value diversity in the workplace environment

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 from the DSI Scientific Director and research collaborators as needed.

Supervision Given

The incumbent will assist the DSI Senior Data Scientists with the supervision and mentoring of junior research trainees (e.g., co-op students).

Minimum Qualifications

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 with relational and non-relational database systems (e.g., SQL, Hive, Cassandra, MongoDB, Spark, Neo4J, Pandas)

Excellent knowledge and hands-on experience with various machine learning packages and models (e.g., PyTorch, Scikit-Learn, TensorFlow)

Excellent knowledge and experience in Natural Language Processing. Knowledge and experience of using pre-traine

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