Data scientist jobs in Toronto, ON and nearby

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

Counted Nov 5, 2026

Hiring at a glance

View jobs

Open jobs: 537
Employers: 248

Advertised starting pay

Average starting payCAD / year: $136,371Across 41 listings
Average starting payCAD / hour: $73.21Across 28 listings

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

Where work happens

Remote: 0%0 listings
Hybrid: 55%297 listings
On-site: 45%239 listings

Not specified: <1% (1 listing)

Employers hiring include TD (38), BMO (11), RBC (11).

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 Toronto, ON and nearby

Within 25 km

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Added 1 month ago
Senior Machine Learning Engineer
Tubi - Canada
Toronto, ON
Added 5 months ago
B
Data Scientist, Tax Transformation Office
BDO
Toronto, Ontario
- Full-time
We are seeking a highly skilled and business-oriented Data Scientist to join the Tax R&D Lab w
Added 5 months ago
D
Senior Data Scientist
DAC
Toronto, Ontario
- Full-time
Move Your Career Forward with DAC a Senior Data Scientist
Added 5 months ago
IF
Data Scientist II
Intact FC
Ajax, Ontario · Toronto, Ontario
- Full-time
Added 4 months ago
V
Senior Specialist, Data Modeler (Microsoft
Vale
Toronto, Ontario
- Full-time
Added 5 months ago
D
Machine Learning Engineer, Detection (TOR)
Doppel
Toronto, ON
- $183,000 to $429,390 CAD / year
- Full-time
Added 6 months ago
IE
Senior Machine Learning Engineer
Index Exchange
Toronto, Ontario
- Full-time
Added 6 months ago
IE
Senior Data Scientist
Index Exchange
Toronto, Ontario
- Full-time
Added 2 months ago
NF
Data Scientist 2
Northbridge Financial Corporation
Toronto, ON
- Full-time
What it’s like to be a Northbridge Data Scientist
Added 2 months ago
Senior Data Scientist - Toronto (m/f/d)
AutoTrader.ca
Toronto, ON
As Senior Data Scientist, you will be key contributor within our global Data Science organization, shaping AI and m
Added 1 month ago
Machine Learning Engineer (Staff & Principal)
Tubi - Canada
Toronto, ON
Added 3 months ago
Data Architect
Konrad
Toronto, Ontario
Added 6 months ago
Data Scientist
Opendoor
Toronto, Ontario
We are seeking an exceptional Senior Data Scientist to join our centralized Data organization. In this role, you will be embedded within our consumer and seller experience groups, working…
Added 2 months ago
Principal Data Scientist (m/f/d)
AutoTrader.ca
Toronto, ON
Join our global Data Science team and take a leadership role in s
Added 6 months ago
Data Scientist
Opendoor
Toronto, Ontario
Opendoor is transforming one of the largest, most complex markets in the world - residential real estate - using data at massive scale. Every pricing signal we generate directly impacts how…

No more jobs.

Doppel

Machine Learning Engineer, Detection (TOR)

Toronto, ON, Canada

$183,000 to $429,390 CAD / year · Full-time

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Job details

Pay: $183,000 to $429,390 CAD / year
Job type: Full-time
Posting language: English
Posted: May 12, 2026

Original job description

Why Join Doppel

Doppel is building the future of social engineering defense. Our AI-native platform uses agentic AI to protect executives, employees, customers, and brands from phishing, impersonation, fraud, and other AI-powered threats across digital channels. We help some of the world’s most recognized brands detect and dismantle attacker infrastructure while strengthening employee resilience through threat-informed training and simulation. By unifying Digital Risk Protection, Human Risk Management and Email Security, Doppel connects threats into a real-time intelligence graph to power faster disruption, smarter defense, and modern security awareness at scale.

Backed by leading investors including Andreessen Horowitz and Bessemer Venture Partners, and trusted by leading enterprises, Doppel is a rapidly growing Series C startup building the future of social engineering defense. Our team combines deep cybersecurity expertise, operational rigor, and startup velocity to solve some of the internet’s most urgent trust and safety challenges.

What We're Building

We're building the AI-native social engineering defense platform.

This means we're designing scalable systems that monitor billions of domains, social media accounts, apps, dark web forums, etc., and leverage AI agents to identify and neutralize digital threats.

What We're Looking For

We’re looking for a machine learning engineer to help build and scale the models and systems that power Doppel’s detection systems. Check out our blog post on how we set up our ML platform. As an MLE at Doppel, you will

Design, train, and deploy models for both batch and real-time inference that identify malicious or infringing content across diverse data sources.
Partner closely with the Detection and Infrastructure teams to ensure our ML systems scale with the volume of web data we ingest
Work on problems that range from NLP and embeddings to similarity search, classification, and anomaly detection
Collaborate directly with customers and internal stakeholders to translate real-world threats into production ML systems

You may be a fit if you:

Have experience building and deploying ML systems in production environments
Are comfortable working with large-scale datasets and distributed data processing frameworks
Understand the trade-offs between research-quality models and production-ready systems
Are excited about solving real-world problems where the adversary is constantly evolving

What We Offer

🚀 A mission-driven culture with low ego, high ownership, deep customer obsession, and exceptional talent density

🍽️ Free lunch and dinner in the office

🌴 Flexible PTO

✈️ Quarterly team offsites

Join Doppel

Doppel is the first platform built to dismantle digital deception at scale. We scan over 150 billion entities daily and deploy continuously adaptive AI SOC agents, paired with expert human analysts, to uncover and disrupt the infrastructure behind phishing, impersonation, and online fraud before attacks can spread. Our Threat Grid turns every customer signal into shared intelligence, making each disruption smarter, faster, and more effective.

We’re not just another cybersecurity company. We’re defining the future of social engineering defense, where trust is protected, and deception becomes unprofitable. Backed by top-tier investors and trusted by some of the world’s most recognized brands, Doppel is growing fast. If you’re driven to solve real-world problems with bold technology, we’d love to meet you.

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More about this job

Responsibilities

Design, train, and deploy ML models for batch and real-time inference to identify malicious content across diverse data sources. Collaborate with Detection and Infrastructure teams to scale systems and translate real-world threats into production ML solutions.

Requirements

Candidates should have experience building and deploying ML systems in production environments using large-scale datasets and distributed frameworks. A strong understanding of the trade-offs between research models and production-ready systems is required.

Skills

Machine Learning
Model Deployment
NLP
Embeddings
Similarity Search
Classification
Anomaly Detection
Distributed Data Processing
Production ML Systems
Large-scale Datasets

Benefits

Free lunch and dinner in the office
Flexible PTO
Quarterly team offsites
Equity

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
NLP
Embeddings
Similarity Search
Classification
Anomaly Detection
Distributed Data Processing
Cybersecurity
Social Engineering Defense
Real-time Inference
Batch Inference
AI Agents
Phishing Detection
Fraud Detection
Production ML
Scalable Systems

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