Data scientist jobs in Vaughan, ON and nearby (528 jobs)

Data scientist jobs within 25 km of Vaughan, ON, Canada. Nearby towns and cities are included. Distances are straight-line, not driving distances.

Counted Nov 8, 2026

Hiring at a glance

View jobs

Open jobs: 528
Employers: 233

Advertised starting pay

Average starting payCAD / year: $138,585Across 38 listings
Average starting payCAD / hour: $72.57Across 27 listings

Employer-advertised starting pay, not employee salaries. Currencies and pay periods stay separate.

Where work happens

Remote: 0%0 listings
Hybrid: 56%294 listings
On-site: 44%233 listings

Not specified: <1% (1 listing)

Employers hiring include TD (40), S M Software Solutions Inc (20), BMO (12).

Sources & calculation notes

These figures describe the listings on this role page at the date shown, not the whole job market. Listings can change.

Employer-listed minimums from at least 10 listings per currency and pay period. These are advertised starting amounts, not employee salaries. Jobs without a minimum and unusual amounts are excluded.

Hybrid and on-site classifications may be inferred from descriptions. Check the original ad. How we count

Data scientist jobs in Vaughan, ON and nearby

Within 25 km

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Added 4 days ago
RC
Supervisor, Data Architect
RSM Canada
Toronto, ON
- Full-time
Added 4 days ago
C
Data Architect/ Data Modeler
Collabera
Toronto, ON
- $70 to $75 CAD / hour
- Contract
Data modeling: Developing conceptual, logical, and physical models for enterprise analytical pla
Added 4 days ago
RU
Supervisor, Data Architect
RSM US LLP
Toronto, ON
- Full-time
Added 4 days ago
7
AI Data Architect
7shifts
Toronto, ON
- $160,000 to $200,000 CAD / year
- Full-time
As the AI Data Architect at 7shifts, you'll design and build how the company ask
Added 4 days ago
AI
Big Data Engineer (PySpark / Spark / Kafka)
Astra-North Infoteck Inc. ~ Conquering today’s challenges, achieving tomorrow’s vision!
Toronto, ON
- Full-time
Job Description: Big Data Engineer (PySpark / Spark / Kafka)
Added 4 days ago
C
Sr. Data Scientist, Fraud Analytics
CIBC
Toronto, ON
- Full-time
As the Sr. Data Scientist, Fraud Analytics, you
Added 4 days ago
CS
Azure data architect
Confiar Services
Toronto, ON
- Contract
We are seeking an experienced Azure Data Architect to design and lead secure, scalable enterprise data solutions on Azure. The ideal candidate will have strong expertise in Azure…
Added 5 days ago
Senior Data Scientist
Conviva
Toronto, ON
Added 5 days ago
C
Senior Data Scientist
Conviva
Toronto, ON
- Full-time
Added 5 days ago
C
Senior Machine Learning Engineer
Clio
Toronto, ON
- Full-time
Added 5 days ago
Data Scientist, FX Quantitative Research
Stripe
Toronto, ON
Added 5 days ago
AI Engineer (Data Scientist)
Hydro One Networks Inc
Toronto, ON
Added 5 days ago
Machine Learning Engineer
Scotiabank
Toronto, ON
Scotiabank is seeking a highly motivated and experienced Senior Manager, Software & Data Engineering to lead the design, development, modernization, and support of critical data and…
Added 5 days ago
CS
Azure data architect
Confiar Services
Toronto, ON
- Contract
We are seeking an experienced Azure Data Architect to design and lead secure, scalable enterprise data solutions on Azure. The ideal candidate will have strong expertise in Azure…
Added 5 days ago
SS
Machine Learning Engineer
Sapphire Stream Technology
Toronto, ON
- Full-time
Added 5 days ago
CS
Data Modeler
Confiar Services
Toronto, ON
- $65 to $70 CAD / hour
- Contract
We are seeking an experienced Data Modeler with strong SQL, data analysis, data modeling, and KYC domain knowledge. The ideal candidate will support data mapping, sanction screening,…
Added 6 days ago
S
Machine Learning Engineer
Syntrace
Toronto, ON
- Full-time
Added 6 days ago
CC
Senior Data Scientist
Computer Consultants International, Inc.
Toronto, ON
- Contract
Data Analytics Specialist/Scientist- RQ11753 (CANADA) - Onsite
Added 8 days ago
H
Machine Learning Engineer
Hays
Toronto, ON
- Contract
Added 8 days ago
CS
Data Architect
Confiar Services
Toronto, ON
- $65 to $70 CAD / hour
- Contract
We are seeking an experienced Azure Data Architect to design and lead secure, scalable enterprise data solutions on Azure. The ideal candidate will have strong expertise in Azure…
Added 8 days ago
T
Machine Learning Engineer II
TD
Toronto, ON
- Full-time
Added 8 days ago
PhD Machine Learning Engineer, Intern
Stripe
Toronto, ON
Added 8 days ago
Master's Machine Learning Engineer, Intern
Stripe
Toronto, ON
Added 8 days ago
CT
Senior Data Scientist, Predictive Modelling
Canadian Tire Corporation
Toronto, ON
- Full-time
The Senior Data Scientist, Predictive Modelling develops predictive and prescriptive solutions that can be integrated into key enterprise decisions (product forecasting and replenishment,…
Added 8 days ago
B
Staff Data Scientist
BMO
Toronto, ON
- Full-time
We are seeking a Staff Data Scientist who combines deep expertise in machine learning with strong software engineering skills and experience building and deploying production-grade ML…

DataVisor

Senior Data Scientist - Fraud Detection

Toronto, ON, Canada

$120,000 to $150,000 CAD / year · Full-time

Apply About employer

Applications open in a new tab.

Job details

Pay: $120,000 to $150,000 CAD / year
Job type: Full-time
Apply by: Apr 25, 2027
Posting language: English
Posted: Oct 2, 2026

Original job description

About DataVisor

DataVisor is the world's leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.

Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us!

Position Overview

We are looking for a Senior-Level Data Scientist to join our Fraud Detection team - someone equally comfortable building production ML models and getting hands-on with individual fraud cases. This is a dual-track role: you'll develop the machine learning systems that catch fraud at scale, and you'll personally lead investigations into how specific fraud attacks happened, reconstructing attacker behavior and turning case-level findings into trend reports and detection improvements. This is a great opportunity to grow your skills in a fast-paced, data-driven environment while making a real, visible impact in the fight against fraud.

Key Responsibilities

Machine Learning & Model Development

End-to-End Model Development: Lead the full lifecycle of fraud detection features and models, from ideation and data exploration to prototyping, productionizing, and monitoring
Advanced Feature Engineering: Develop highly predictive features from complex, large-scale, multi-dimensional data, including user behavior, device intelligence, network graphs, and transaction records
Large-Scale Data Processing: Work with massive, noisy, and imbalanced datasets (billions of events) using tools like Spark, SQL, and our proprietary AI platform
Agentic AI & Automation: Leverage agentic AI to automate analytic pipelines and develop reusable skill tools that accelerate fraud investigation, feature generation, and reporting workflows

Live Fraud Investigation & Reporting

Lead investigations into complex fraud cases across identities, accounts, devices, and transaction surfaces. Reconstruct attacker sequences and hypothesize actor intent and tooling
Produce clear, evidence-backed technical reports and case studies for product, engineering, operations, legal, and executive stakeholders
Generate fraud trend reports for customers, synthesizing case-level findings and aggregate data into narratives customers can act on

Requirements

Qualifications

Master's or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.

3+ years of applied experience in fraud detection, cybersecurity, or a related adversarial/high-velocity risk domain (fintech, consumer payments, banking, SaaS, marketplace risk, or security research)
Solid understanding of both classic machine learning models (Logistic Regression, Gradient Boosting, etc.)
Hands-on experience with the machine learning lifecycle in a production environment
Investigator mindset: demonstrated skill in pattern synthesis, hypothesis testing, and triaging signal from noise in ambiguous, adversarial cases - not just building and monitoring models
Strong programming skills in Python (must-have) and proficiency with SQL; experience with PySpark is a significant plus
Experience with large-scale data tools (Spark, Hadoop, etc.) and cloud platforms (AWS, GCP, Azure)
Excellent communication skills - able to explain complex, ambiguous, or technical behavior clearly to both technical and non-technical audiences, including customers and executives
Professional proficiency in written and spoken English, with the ability to collaborate effectively in a global, cross-functional team

Benefits

Base salary range: $120,000-$150,000, commensurate with experience
PTO, Stock Options, Health Benefits

Apply About employer

More about this job

Responsibilities

Develop, productionize, and monitor fraud detection models and features using large-scale, complex data, and apply agentic AI to automate analytic and investigation workflows. Lead investigations into fraud cases, reconstruct attacker behavior, and produce evidence-based case studies and customer trend reports.

Requirements

Requires a master's or PhD in a quantitative field and at least three years of applied experience in fraud detection, cybersecurity, or a related adversarial risk domain. Candidates need production machine learning experience, strong Python and SQL skills, familiarity with large-scale data tools and cloud platforms, an investigative mindset, and excellent communication skills.

Skills

Fraud Detection
Machine Learning
Feature Engineering
Fraud Investigation
Python
SQL
PySpark
Apache Spark
Large-Scale Data Processing
Data Analysis
Pattern Recognition
Hypothesis Testing
Agentic AI
Technical Reporting
Cloud Platforms
Communication

Benefits

Paid Time Off
Stock Options
Health Benefits

Visa sponsorship

Not detected in the job text

Keywords

Fraud Detection
Cybersecurity
Machine Learning
Logistic Regression
Gradient Boosting
Python
SQL
PySpark
Apache Spark
Hadoop
AWS
GCP
Azure
Agentic AI
Feature Engineering
Device Intelligence
Network Graphs
Transaction Records
Fraud Investigation
Pattern Synthesis
Hypothesis Testing
Imbalanced Datasets
Large-Scale Data Processing
Production Machine Learning
Risk Management
Fintech
Consumer Payments
Banking
SaaS
Marketplace Risk

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