Data Scientist (NLP)

Staff - Non Union

Job 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 Date
March 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

The DSI is a Faculty of Science research institute designed to incubate and accelerate research, innovation and training in data-intensive science. Working across the university's data science community and advanced computing teams, the DSI focuses on building interdisciplinary research teams tackling data-rich problems. We specialize in diverse application domains such as healthcare analytics, data-centric manufacturing, housing analysis, and many others. At the DSI, we offer a welcoming and friendly work environment with excellent benefits where you can solve complex data challenges to benefit society.

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.

• Contribute to curriculum and workshop development in data science and health

• 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 minimal 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).
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 in Natural Language Processing. Knowledge and experience of using pre-trained language models is a bonus

• 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)

• Knowledge and hands-on experience developing interactive visuals

• Experience developing workflows and models on cloud platforms (e.g., Azure, Google Cloud, AWS)

• Excellent communication skills and able to explain complex concepts to non-technical audiences

• Excellent organizational skills and able to juggle multiple projects

• Experience in project management is an asset but not necessary

• Experience working in health is an asset but not necessary