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 4, 2026

Hiring at a glance

View jobs

Open jobs: 523
Employers: 243

Advertised starting pay

Average starting payCAD / year: $132,249Across 37 listings
Average starting payCAD / hour: $72.15Across 26 listings

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

Where work happens

Remote: 0%0 listings
Hybrid: 55%286 listings
On-site: 45%236 listings

Not specified: <1% (1 listing)

Employers hiring include TD (37), 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 2 months ago
AI and Data - Data Architect (Databricks)
EY
Toronto, ON
We are seeking a Manager/ Data Architect for our AI & Data practice team. We are looking for a candidate with strong technical
Added 2 months ago
L
Sr Data Scientist II
LexisNexis
Toronto, ON
- Full-time
Added 2 months ago
S
Lead Data Scientist
Sanofi
Toronto, ON
- Full-time
Added 2 months ago
PX
Consultant, Data Scientist (Cortex AI)
Project X Ltd.
Toronto, ON
- Full-time
Project X Ltd. builds high-performing teams of talented, client-focused problem solvers who thrive on complex data challenges. Guided by our values of Care, Bravery, Excellence, and…
Added 2 months ago
SG
Senior Machine Learning Engineer
SCIENTIFIC GAMES
Toronto, ON
- Full-time
…We push game designs to the next level and are pioneers in data analytics and iLottery. Built on a foundation of trusted partnerships, Scientific Games combines relentless innovation,…
Added 2 months ago
SG
Senior Data Scientist
SCIENTIFIC GAMES
Toronto, ON
- Full-time
…We push game designs to the next level and are pioneers in data analytics and iLottery. Built on a foundation of trusted partnerships, Scientific Games combines relentless innovation,…
Added 2 months ago
D
Manager, Data Architect
dentsu
Toronto, ON
- Full-time
Our mission is to Drive Business Performance. We use data to create personalized and connected experiences that deliver transformative business outcomes. Our role is to ensure our clients…
Added 2 months ago
Data Scientist, Optimization - Real-Time Supply Management
Lyft
Toronto, ON
Data Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation…
Added 1 month ago
Data Architect
Capco
Toronto, ON
Capco is looking for an experienced Data Architect with deep expertise across data flows, data integration, data sources, and enterprise data architecture. You’ll work with clients to…
Added 2 months ago
E
Machine Learning Engineer
eBay
Toronto, ON
- Full-time
Added 2 months ago
G
Machine Learning Engineer
GPTZero
Toronto, ON
- $120,000 to $160,000 CAD / year
- Full-time
Added 1 month ago
Q
Sr to Principal Machine Learning Engineer, Framework & Performance
Qualcomm
Markham, ON
- Full-time
Added 2 months ago
I
Data Architect
ICES
Toronto, ON
- Full-time
ICES is a world-leading health research and analytics institute. With a wealth of data and analytic expertise, we create trusted evidence that has changed health policy and practice and…
Added 2 months ago
V
Machine Learning Engineer Lead
Vancity
Toronto, ON
- Full-time
Added 2 months ago
PX
Data Scientist (AI/ML)
Project X
Toronto, ON
- Full-time
Project X Ltd. builds high-performing teams of talented, client-focused problem solvers who thrive on complex data challenges. Guided by our values of Care, Bravery, Excellence, and…
Added 2 months ago
SG
Senior Machine Learning Engineer
Scientific Games
Toronto, ON
- Full-time
…We push game designs to the next level and are pioneers in data analytics and iLottery. Built on a foundation of trusted partnerships, Scientific Games combines relentless innovation,…
Added 2 months ago
SG
Senior Data Scientist
Scientific Games
Toronto, ON
- Full-time
…We push game designs to the next level and are pioneers in data analytics and iLottery. Built on a foundation of trusted partnerships, Scientific Games combines relentless innovation,…
Added 2 months ago
F
Data Scientist (ML Engineer)
Flywheel
Toronto, ON
- Full-time
Added 1 month ago
Staff Machine Learning Engineer, Generative AI (Auth0)
Okta
Toronto, ON
Added 3 months ago
S
Data Architect - Canada Region
Slalom
Toronto, ON
- Full-time
Added 2 months ago
CG
Senior Machine Learning Engineer, Causal & Decision Systems
CSC Generation
Toronto, ON
- Full-time
…transform them with Genesis, our operating platform combining a Data Fabric, Automation Engine, proprietary tools, and shared services to modernize operations, elevate customer experience,…
Added 2 months ago
SM
Senior Data Scientist
Spin Master
Toronto, ON
- Full-time
Added 3 months ago
EL
Fraud Data Scientist
EnStream LP
Toronto, ON
- Full-time
Reports to: Head of Applied AI & Data Engineering
Added 3 months ago
ES
Machine Learning Engineer - Express Scripts Canada
Express Scripts Pharmacy Benefit Services
Mississauga, ON
- Full-time
Added 2 months ago
S1
Full-Stack Machine Learning Engineer
Signal 1
Toronto, ON
- Full-time

CSC Generation

Senior Machine Learning Engineer, Causal & Decision Systems

Toronto, ON, Canada

Full-time

Apply About employer

Applications open in a new tab.

Job details

Job type: Full-time
Posting language: English
Posted: Aug 15, 2026

Original job description

CSC Generation is the AI-native holding company re-engineering omnichannel retail. We acquire iconic brands and transform them with Genesis, our operating platform combining a Data Fabric, Automation Engine, proprietary tools, and shared services to modernize operations, elevate customer experience, and expand margins. With $1B+ in revenue across 13 brands, our portfolio includes Sur La Table, Backcountry, One Kings Lane, and others that serve as real-world innovation labs.

Reports to: CTO

Location: Hybrid- Toronto, ON

\nAbout the Role

CSC Generation is building closed-loop decision systems that use machine learning to operate consumer businesses more intelligently. We are starting with pricing and expanding into areas such as inventory, purchasing, promotions, marketing, and assortment.

You will help build systems that estimate causal response and quantify uncertainty, choose actions, generate useful information, observe outcomes, update policies, evaluate challengers, and deploy within guardrails.

We want to answer questions such as:

What happens because we change a price, rather than simply what happens next?
How should uncertainty affect a decision?
When should the system exploit what it knows versus experiment to learn?
Can we estimate the value of a challenger policy before fully deploying it?
How do we optimize economic outcomes while respecting inventory, margin, vendor, customer, and operational constraints?

What You'll Do

Depending on your background, you may work across:

Causal and heterogeneous treatment-effect modeling
Uncertainty estimation and calibration
Contextual bandits, active learning, or sequential decision-making
Policy learning and constrained optimization
Counterfactual and off-policy evaluation
Experimentation and champion/challenger systems
Production ML infrastructure, monitoring, and automated deployment

We care about selecting the right method, not using a particular framework.

What Success Looks Like

Success is not a better offline metric.

The systems you build should produce measurable economic lift in controlled experiments, generalize across businesses, learn from their own interventions, and safely automate an increasing share of real commercial decisions.

Over time, the goal is simple:

the system should become better at operating the business because it has operated the business.

What We're Looking For

We care more about exceptional technical ability and judgment than matching a checklist. Strong candidates will have experience in several of:

Machine learning and statistical modeling
Causal inference and experimentation
Recommendation, advertising, pricing, marketplace, credit, or other decision systems
Bandits, reinforcement learning, optimization, or active learning
Uncertainty estimation
Counterfactual evaluation
Production ML systems
Python, SQL, and large behavioral datasets

Why This Role Is Different

Most ML systems learn from a dataset. Here, the decisions made by the model influence the data the model sees next. That creates a continuous loop: decision, intervention, outcome, learning, better decision.

The long-term opportunity is to build that capability once and apply it across a portfolio of businesses and increasingly broad commercial decisions.

Real-world impact. The systems you build will run live commercial decisions across a portfolio of consumer brands, so you will see measurable economic outcomes from your work, not just offline benchmark improvements.
Technical growth at the frontier. Causal decision systems that learn from their own interventions are still an open problem. You will work at the intersection of causal ML, bandit algorithms, and production engineering, with the latitude to choose the right method for the problem.
Full ownership. You will own problems end to end, from framing and modeling through production deployment and evaluation.
Competitive benefits. Comprehensive health, dental, and vision coverage; RRSP matching; paid time off; and access to cross-brand employee discounts across the CSC Generation portfolio.

Interview Process

Recruiter Screen: A conversation with our recruiting team to cover your background, the role, and mutual fit.
Virtual Interview Rounds: Focused discussion with the hiring manager & deeper conversations with cross-functional engineering and data science collaborators covering technical depth, system design, and working style.
In-Person Interview: A final on-site visit at our Toronto office to meet the broader team and connect with key stakeholders.
Reference Checks: Conducted in parallel with the final stages where possible.
Offer: We move quickly for the right candidate.

Interview process is subject to change. Any updates will be shared promptly and clearly.

Please Note

Part of our interview process is a mandatory in-person interview with someone on our team prior to an offer. Candidates that are unwilling or unable to meet for an in-person interview will be removed from consideration immediately.
Due to a high volume of fraudulent applications, you must share a valid LinkedIn profile URL in the application questions below to be considered. If you do not have a LinkedIn profile, you must provide a credible reason in that field and supply alternative evidence of your professional background to verify your identity.

CSC Generation is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law.

The CSC Generation family of brands is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need assistance or accommodation due to a disability, please contact hrbenefits@cscshared.com.

For Ontario applicants, please note that this posting is for an existing vacancy.

CSC Generation will conduct an exhaustive background check including verifying dates of employment directly with your former employer.

Apply About employer

More about this job

Responsibilities

You will build closed-loop decision systems that estimate causal responses and quantify uncertainty to automate commercial decisions. The role involves developing models for pricing, inventory, and marketing while ensuring systems learn from their own interventions.

Requirements

Strong candidates should have exceptional technical ability in machine learning, causal inference, and statistical modeling. Experience with production ML systems, Python, SQL, and decision-making frameworks like bandits or reinforcement learning is highly valued.

Skills

Machine learning
Causal inference
Statistical modeling
Python
SQL
Reinforcement learning
Bandits
Optimization
Uncertainty estimation
Counterfactual evaluation
Production ML systems
Active learning
Constrained optimization
Experimentation
Policy learning

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
Causal Inference
Decision Systems
Pricing
Inventory Management
Python
SQL
Reinforcement Learning
Bandits
Active Learning
Optimization
Counterfactual Evaluation
Uncertainty Estimation
Production ML
Automated Deployment
Heterogeneous Treatment-Effect Modeling
Policy Learning
Experimentation
Data Science
Statistical Modeling

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