Junior NLP Data Scientist

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

Job End Date

This position will be filled internally. It is posted for informational purposes only.

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 Department of Psychiatry at the University of British Columbia (UBC) is seeking a full-time Junior NLP Data Scientist to join a dynamic, interdisciplinary research program focused on applying artificial intelligence to psychiatry and supportive cancer care.

Under the supervision of Dr. John-Jose Nunez - a dual-trained psychiatrist and computer scientist, Dr. Kristin Campbell, Professor at the Department of Physical Therapy and Dr. Lauren Capozzi, Assistant Professor at the Department of Medicine, the successful candidate will work in close collaboration with BC Cancer. They will contribute to the technical development of research and clinical tools that use natural language processing (NLP) and machine learning to improve the psychosocial health of patients and enhance care provided by clinicians.
Organizational Status
The Junior NLP Data Scientist receives direct direction and reports to the Principal Investigators, Dr. John-Jose Nunez, Assistant Professor at Department of Psychiatry, Dr. Kristin Campbell, Professor at the Department of Physical Therapy and Dr. Lauren Capozzi, Assistant Professor at the Department of Medicine. The Data Scientist will also interact with other lab members, research assistants, trainees, and members of other departments at UBC and BC Cancer. They will help coordinate the activities of student developers on the team.
Work Performed

- Help with designing and developing predictive and generative NLP pipelines using clinical data.

- Assist with front-end and back-end engineering for digital health applications.

- Assist with building and maintaining secure, scalable cloud infrastructure for deploying AI models (e.g., AWS).

- Assist with researching state-of-the-art techniques in NLP, machine learning, and ethical AI.

- Collaborate with physicians, patients, developers, and researchers to co-design and evaluate clinical tools.

- Support and at times lead the preparation of peer-reviewed manuscripts, conference abstracts, grant proposals, ethics submissions, and other scientific documentation.

- Assist with coordinating student software developers, and liaise with research assistants.
Consequence of Error/Judgement
The Data Scientist receives direction and reports to the Principal Investigators. Errors in accuracy, judgement, tact and poor decisions could delay the timely completion of the projects or be damaging to the reputation, for the PIs, the Department, Faculty, UBC and other institutions affiliated with the project(s). The Principal Investigator will help with quality assurance and review work to mitigate these risks.
Supervision Received
Works under supervision and receives detailed instructions on assignments. Work is reviewed in terms of completeness, accuracy and timeliness. 
Supervision Given
The position may involve the supervision of learners who join the laboratory, generally involving data science and programming tasks.
Minimum Qualifications
Undergraduate degree in a relevant discipline. Minimum of one year of related experience, 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

• Experience with NLP libraries and toolkits (e.g., Hugging Face, spaCy, NLTK).
• - Strong programming skills (Python preferred), with experience in ML and data science frameworks (e.g., PyTorch, TensorFlow, Pandas).
• - Experience with cloud-based platforms (e.g., AWS, GCP) and containerization tools (e.g., Docker).
• - Demonstrated ability to deliver on assignment programming and data science tasks and to work collaboratively within multidisciplinary teams.
• - Track record of preparing or contributing to scientific publications.
• - Experience working with healthcare or clinical datasets, particularly in oncology or psychiatry.
• - Knowledge of privacy regulations and responsible AI practices in healthcare.
• - Experience with digital health research, usability testing, or user-centered design.
• - Industry or academic experience applying AI in healthcare settings.