Data scientist jobs in Mississauga, ON and nearby (546 jobs)

Data scientist jobs within 25 km of Mississauga, 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: 546
Employers: 247

Advertised starting pay

Average starting payCAD / year: $136,636Across 40 listings
Average starting payCAD / hour: $72.74Across 29 listings

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

Where work happens

Remote: 0%0 listings
Hybrid: 57%309 listings
On-site: 43%236 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 Mississauga, ON and nearby

Within 25 km

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Added 1 month ago
HI
Data Scientist
HISH IT SERVICES
Toronto, ON
- $85 CAD / hour
- Contract
Added 1 month ago
M
I&IT Data Scientist I
Metrolinx
Toronto, ON
- Full-time
Added 1 month ago
Senior Machine Learning Engineer, Recommendations
Lyft
Toronto, ON
With a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Marketplace, Growth, and beyond.…
Added 1 month ago
Senior Data Scientist I
Bell
Toronto, ON
Added 1 month ago
AT
lead data scientist
ApoSys Technologies Inc.
Mississauga, ON
- Full-time
Added 1 month ago
CC
Data Scientist
Coca-Cola Canada Bottling Limited
Toronto, ON
- Full-time
Added 1 month ago
Data Scientist
CONA Services
Toronto, ON
Added 1 month ago
Data Scientist
CONA Services
Toronto, ON
Added 1 month ago
AC
Data Scientist
Aviva Canada
Toronto, ON
- Full-time
Added 1 month ago
S
Data Scientist Intern (Jan 2027 12 Months)
SOTI
Mississauga, ON
- Full-time
As a Data Scientist Intern at SOTI, you’ll have the opportunity to work alongside experienced Data Scientists and Engineers on real-world AI and Machine Learning initiatives that support…
Added 1 month ago
CL
Data Scientist
Charger Logistics Inc.
Brampton, ON
- Full-time
Added 1 month ago
Data Scientist
Aviva
Toronto, ON
Added 1 month ago
Scientifique principal des données I
Bell
Toronto, ON
Added 1 month ago
TR
Lead Data Scientist, Customer & Growth Analytics
Thomson Reuters
Toronto, ON
- Full-time
Thomson Reuters Legal is seeking a Lead Data Scientist to help power data-driven growth and adoption of our AI-enabled legal solutions. In this role, you will design, build, and maintain…
Added 1 month ago
H
Data Architect, Enterprise Data Management
Hays
Toronto, ON
- Contract
Our client is a leading Canadian financial services organization undergoing a significant enterprise data transformation. As part of its modernization journey, the organization is investing…
Added 1 month ago
Senior Data Scientist
Momentum Financial Services Group
Toronto, ON
Added 1 month ago
T
R&D Engineer- Data Scientist
Tenova
Mississauga, ON
- Full-time
The R&D Engineer - Data Science, under the direction of the R&D Manager, is responsible for analyzing operational and test data, developing algorithms, and researching, building,…
Added 1 month ago
T
Data Architect, Technology Data Management
TD
Toronto, ON
- Full-time
Added 1 month ago
T
Data Scientist II
TD
Toronto, ON
- Full-time
Added 1 month ago
T
Data Scientist II
TD
Toronto, ON
- Full-time
Added 1 month ago
V
Senior Data Scientist
Visa
Toronto, ON
- Full-time
Added 1 month ago
D
Data Scientist, Data valorization
Desjardins
Mississauga, ON · Toronto, ON
- Full-time
As a data scientist, you provide the data needed to make business decisions, develop solutions and services adapted to business issues and understand member and client behaviour. You lead…
Added 1 month ago
AI and Data - Data Architect - Healthcare
EY
Toronto, ON
We are seeking a Data Architect for our AI & Data practice team. We are looking for a candidate with strong technical leadersh
Added 1 month ago
E
Data Scientist
eBay
Toronto, ON
- Full-time
Added 1 month ago
I
Principal Data Scientist, Product Data & Analytics
Intuit
Toronto, ON
- Full-time
We are seeking a Principal Data Scientist to lead I

Stripe

PhD Data Scientist, Intern

Toronto, ON, Canada

Apply About employer

Applications open in a new tab.

Job details

Posting language: English
Posted: Oct 1, 2026

Original job description

Who we are

About Stripe

Stripe is a technology company focused on improving the conditions for economic growth and prosperity. We build programmable financial infrastructure, rethinking from first principles how financial services should work, to make it easier and cheaper for any business to start and scale. More than 10 million businesses build on Stripe, spanning the economic frontier - from solo founders to established enterprises - united by a practical focus on growth. The most ambitious companies in the world use Stripe as core infrastructure to grow faster. They process trillions of dollars a year on Stripe, equivalent to around 1.6% of global GDP. While economic growth makes everyone better off, open markets also enable greater variety. When any business can easily serve a global customer base, the quality and diversity of products in the world increase, and craft and creativity are unleashed into the smallest niches. Our own growth is wholly contingent on the success of the businesses building on Stripe. We therefore invest back into our technology at an unusual rate. We make upgrades to our products every single day to deliver compounding gains to our customers. We maintain some of the most reliable APIs on the internet. We build entirely new pieces of financial infrastructure to enable new ideas. And our significant advances in risk and fraud infrastructure over many years are making the internet economy safer and more accessible.

Though people at Stripe don’t tend to take themselves seriously, Stripe is a fairly serious place: our customers are depending on us for their livelihoods. We admire ambition, intensity, curiosity, humility, and rigor. The most effective people become knowledgeable about many domains besides their own. Any company is an applied exercise in understanding some aspect of society or the market. In working with so many (especially the new and innovative ones), we think that Stripe is one of the very best places to learn about how the world works.

About the team

Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. We're looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact. Our Fraud, Losses, and Financial Crime Data Science team builds the models and data products that protect Stripe and its users from fraud, account takeover, and financial crime. We own the full fraud and loss modeling stack - from account takeover detection and card fraud classification to merchant-level loss estimation, unsupervised anomaly detection, and financial crime risk modeling. We partner with Fraud Engineering, Financial Crimes Engineering, and Risk Operations to bring these systems into production and ensure they have measurable impact on Stripe's financial integrity and user trust.

What you’ll do

As an intern at Stripe you’ll work on projects across our stack that directly impact the way millions of businesses operate. You’ll own problems end to end with the support of your manager and teammates. It’s an opportunity to work alongside some of the most creative and technically rigorous data analysts and scientists in the industry. You'll partner deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. You'll work closely with partners to extract insights from the rich and complex data at Stripe. You'll build metrics, scalable data pipelines, dashboards, and reports to inform and run the business. You'll deliver actionable business recommendations through analyses and data storytelling.

Our internship program is competitive and the expectations are high.

Responsibilities

Applying probability distributions, statistical inference, and hypothesis testing to quantify uncertainty and evaluate business outcomes
Using Python or R for data analysis, data processing, visualizations, statistical modeling, machine learning, predictive analytics, automation, and implementing causal inference and experimental analyses
Building, training, and evaluating predictive models across regression and classification tasks for bias-variance trade-offs and model selection
Modeling temporal dependencies, seasonality, and trend decomposition to generate and evaluate time-series predictions
Identifying structural patterns, clusters, and outliers in unlabeled data
Deploying models in production and adjusting model thresholds to improve performance
Designing, running, and analyzing complex experiments and leveraging causal inference designs
Using SQL and Spark to create, transform, and analyze large datasets
Learn quickly by asking great questions, finding how to work with your mentor and teammates effectively, and communicating the status of your work clearly
Present your work to the Data Science team, partner teams, and fellow interns.

Who you are

Ambitious builder: You’re energized by building solutions without clear precedent and solving problems with far-reaching consequences. Successful Stripes are deeply curious, and prefer the joy of discovery to the comfort of certainty.
Rigorous thinker: You appreciate that things worth doing are rarely simple. You enjoy working on problems that have never been tackled before.
Adaptable problem solver: You adapt quickly and treat obstacles as opportunities. At Stripe we embrace kindness while encouraging Stripes to take measured risks and act boldly, even in the absence of consensus.

Minimum requirements

Enrolled in a quantitative PhD program (e.g. Data Science, Statistics, Economics, Mathematics, etc.) with the expectation of graduating in December 2027 or spring/summer 2028
Experience with SQL and a scientific computing language (such as Python, R, etc.)
Proficiency with AI tools to accelerate model development, analysis, and coding
Experience communicating and collaborating with multidisciplinary stakeholders in a team environment

Preferred qualifications

Experience writing and debugging data pipelines
Demonstrated ability to evaluate and receive feedback from mentors, peers, and stakeholders via experience from previous internships or other multi-person projects
Ability to learn new systems and form an understanding of those systems, through independent research and working with a mentor and subject matter experts

Apply About employer

More about this job

Responsibilities

The intern will build and deploy machine learning models and data products to protect Stripe from fraud and financial crime. They will also partner with cross-functional teams to extract insights, build scalable data pipelines, and deliver actionable business recommendations.

Requirements

Candidates must be enrolled in a quantitative PhD program with an expected graduation date in 2027 or 2028. Proficiency in SQL and a scientific computing language like Python or R is required.

Skills

Python
R
SQL
Spark
Machine Learning
Statistical Modeling
Predictive Analytics
Causal Inference
Experimental Design
Data Pipelines
Time-series Analysis
Anomaly Detection
Data Visualization
Hypothesis Testing
Probability Distributions

Visa sponsorship

Not detected in the job text

Keywords

Data Science
Machine Learning
Python
R
SQL
Spark
Fraud Detection
Financial Crime
Statistical Inference
Predictive Modeling
Causal Inference
Time-series Analysis
Data Pipelines
Anomaly Detection
Experimental Design
Data Storytelling
Risk Modeling
Financial Infrastructure
Quantitative Analysis
Regression
Classification
Bias-variance Trade-off
Automation
Dashboarding
Data Processing

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