Data Analyst Research Assistant

Staff - Non Union

Job Category
Non Union Technicians and Research Assistants

Job Profile
Non Union Salaried - Research Assistant /Technician 2

Job Title
Data Analyst Research Assistant

Department
Talhouk Laboratory | Department of Obstetrics & Gynaecology | Faculty of Medicine

Compensation Range
$4,207.63 - $5,005.45 CAD Monthly

Posting End Date
June 1, 2024

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

Job End Date

May 31, 2025

This position is located within a health-care facility, therefore, the successful candidate will be required to provide verification of full vaccination against Covid-19 provided prior to the start date, as required by a provincial health mandate.

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

BC’s Gynecologic Cancer Initiative is an interdisciplinary team working together to drive innovative research that transforms how we prevent, diagnose, treat and improve survivorship care for people with or at risk of gynecological cancer. We are seeking a data analyst with a strong background in R and Python. The candidate will participate in developing, improving, maintaining, and using bioinformatics tools for a processing pipeline.

The role is well suited for a creative individual with a passion for software development and data analysis within an academic setting.
Organizational Status
The data analyst will report directly to Dr. Aline Talhouk and will receive daily oversight from the Computational Biologist. The incumbent is expected to work independently.
Work Performed

- Perform statistical analysis for clinical data and processed sequencing data

- Automate data cleaning and processing workflows

- Contribute to data management activities

- Develop, improve, and maintain high-throughput data processing workflows, primarily in R and Python, and adapt to other languages as necessary

- Research, evaluate and integrate new technologies, algorithms, and platforms as needed

- Apply software engineering best practices to create, test, and deploy new improvements and features to existing software

- Document statistical analysis results, workflows, standard operating procedures (SOPs), and other processes and procedures as required

- Knowledgeable in utilizing and comprehending common machine learning techniques.

- Collaborate effectively with other researchers to foster a productive and positive work environment

- Perform additional tasks as required to support the team’s objectives

Consequence of Error/Judgement
The applicant will be granted substantial independence in their role and must demonstrate exceptional judgment, responsibility, and initiative in conducting data analysis and ensuring the successful and timely completion of tasks. High-level decisions will be subject to approval by the supervisor.
Supervision Received
The successful candidate will report to Dr. Aline Talhouk and the Computational Biologist.
Supervision Given

The successful candidate may help to supervise undergraduate trainees.

Minimum Qualifications
High school graduation, some additional training in a related field and a minimum two years of related experience or an 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

- Undergraduate or graduate degree in a relevant discipline 

- Minimum of an Undergraduate degree or technical diploma in computer science or a similar quantitative discipline

- Proven expertise with R and Python mandatory 

- Proven expertise in software engineering best practices, including version control, issue tracking and quality assurance 

- Comfortable working in a Unix environment, including experience with shell scripting and common command-line tools 

- Demonstrated interpersonal skills including the ability to work effectively with others in a team environment 

- Demonstrated ability to efficiently organize assignments and establish priorities