Senior Data Scientist - Fraud Detection
- Employment type
- Full-time · On-site
- Posted
- September 25, 2026
- NOC code
- 21211 — Data scientists
- Province
- British Columbia (BC)More in British Columbia
Hiring confidence: Sparse posting · 11/100
This posting is missing most of the signals we look for, or shows patterns common to listings that are not actively being filled. Check with the employer before applying. How this is scored
Job Overview
This role is based in British Columbia. The Canadian NOC code for this position is 21211 — Data scientists. DataVisor is hiring for this full-time position through Jobily, where you can check how well your resume matches the posting before you apply.
Market context
About this role in British Columbia
Average salary for Data Scientist in British Columbia
Median $67,500 per year, with most postings between $67,500 and $71,250 (Data scientists, 2026-05, 7 postings). This posting does not state a salary.
NOC code
21211 — Data scientists. The National Occupational Classification code is what Express Entry, provincial nominee programs and Job Bank use to identify this occupation.
Typical qualifications for Canadian employers
A master's or bachelor's degree in a quantitative field, plus Python or R, statistical modelling and experience shipping models to production.
Licensing: No licence or registration is required.
Fit check
Is this role right for you?
Top skills this posting asks for:
- Machine Learning
- Data Science
- Fraud Detection
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What you'll do
- Develop and implement fraud detection algorithms
- Build machine learning models for real-time fraud identification
- Analyze fast-evolving fraud and money laundering activities
- Work with SaaS platform for data consolidation and enrichment
- Collaborate on AI-powered fraud and risk solutions
- Improve detection coverage and model performance
What you'll need
- Senior-level experience in data science or machine learning
- Experience with fraud detection or risk management systems
- Strong background in unsupervised machine learning techniques
- Proficiency in statistical analysis and modeling
- Experience working with large-scale data platforms
- Knowledge of anti-money laundering (AML) concepts