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Statistical Data Scientist Jobs in Toronto, ON (NOW HIRING)

Stripe

Data Scientist

Toronto, ON · On-site

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 work is broad and varied ...

Royal Bank of Canada

Data Scientist

Toronto, ON

Support the development and deployment of statistical / AI / ML solutions, working in a team of data scientists and data engineers. * Collect, transform, and analyze large datasets (structured and ...

Achievers

Data Scientist

Toronto, ON

Advanced degree in Statistics, Computer science, Behavioural Science or Mathematics preferred * 3+ years of experience analyzing product's data, building AI/ML algorithms or making product focused ...

Charger Logistics Inc

Data Scientist

Brampton, ON · On-site

Bachelor's degree or equivalent in Data Analytics, Statistics, Mathematics, or Computer Science. * 4+ years of hands-on experience in data science and machine learning, delivering production-grade ML ...

New

Intact Financial

Data Scientist II

Mississauga, ON · On-site

Apply sound statistical and machine learningmethodology(e.g., experiment design,appropriate ... Maintain and improve data science tools and platforms, helping ensure efficiency, reliability, and ...

Intact Financial

Data Scientist II

Toronto, ON · On-site

Apply sound statistical and machine learningmethodology(e.g., experiment design,appropriate ... Maintain and improve data science tools and platforms, helping ensure efficiency, reliability, and ...

Intact Financial

Data Scientist II

Ajax, ON · On-site

Apply sound statistical and machine learningmethodology(e.g., experiment design,appropriate ... Maintain and improve data science tools and platforms, helping ensure efficiency, reliability, and ...

Td

Data Scientist III

Toronto, ON

CA$96.90K - CA$136.80K/yr

As a Data Scientist in Real Estate Secured Lending, you will be responsible for leading the ... Lead development, validation, and maintenance of pricing models using statistical, machine learning ...

Massive Insights Inc.

Senior Data Scientist

Toronto, ON · On-site

As a Senior Data Scientist, you will work with diverse datasets across various industries, utilizing your expertise in statistical analysis, machine learning, and predictive modeling to address our ...

Hibernian General Insurance

Data Scientist

Toronto, ON

CA$80K - CA$120K/yr

As a Data Scientist on the Fraud Data Science team , you'll work closely with a wide range of ... Your work will include building and deploying data pipelines, machine learning, and statistical ...

Hibernian General Insurance

Data Scientist

Markham, ON

CA$80K - CA$120K/yr

As a Data Scientist on the Fraud Data Science team , you'll work closely with a wide range of ... Your work will include building and deploying data pipelines, machine learning, and statistical ...

Td

Data Scientist II

Toronto, ON

CA$81.60K - CA$115.20K/yr

As a Data Scientist in Real Estate Secured Lending, you will be responsible for developing ... Develop, validate, and maintain pricing models using statistical, machine learning, and data mining ...

Canadian Tire

Senior Data Scientist

Toronto, ON · On-site

Statistics is your strong suit. You have a strong command of machine learning, data science and software engineering. Youu2019re analytical, a problem-solver, detail-oriented and enjoy working in a ...

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How much do statistical data scientist jobs pay per hour?

As of May 28, 2026, the average hourly pay for statistical data scientist in Toronto, ON is $46.97, according to ZipRecruiter salary data. Most workers in this role earn between $31.43 and $60.10 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Statistical Data Scientist, and why are they important?

To thrive as a Statistical Data Scientist, you need a strong background in statistics, mathematics, and data analysis, typically supported by a degree in a quantitative field. Proficiency with programming languages like Python or R, data visualization tools, and experience using machine learning libraries and statistical software such as SAS or SPSS are highly valuable. Critical thinking, problem-solving, and the ability to communicate complex findings clearly are essential soft skills for this role. These competencies ensure that insights derived from data are accurate, actionable, and effectively inform business or research decisions.

How does a Statistical Data Scientist typically collaborate with cross-functional teams on data-driven projects?

Statistical Data Scientists often work closely with cross-functional teams, including engineers, business analysts, and domain experts, to translate complex data into actionable insights. They play a key role in designing experiments, developing statistical models, and ensuring data integrity. Effective communication is essential, as they must explain technical findings to non-technical stakeholders and adapt their analyses to support business objectives. Regular collaboration through meetings, code reviews, and presentations is common, making teamwork and adaptability vital skills in this role.

What does a Statistical Data Scientist do?

A Statistical Data Scientist uses statistical methods and computational tools to analyze large and complex datasets, uncover trends, and generate actionable insights for organizations. They design experiments, build predictive models, and interpret data to solve business problems or advance scientific research. Their work often involves cleaning and preparing data, choosing appropriate statistical techniques, and communicating findings to stakeholders through reports and visualizations.

Is 30 too late for data science?

A statistical data scientist can start a career at age 30, as the field values skills such as programming, statistical analysis, and machine learning, which can be developed through self-study, bootcamps, or advanced degrees. Many professionals transition into data science later in their careers, and age is generally not a barrier if relevant skills and experience are acquired.

What is the difference between Statistical Data Scientist vs Data Analyst?

AspectStatistical Data ScientistData Analyst
Required CredentialsDegree in Statistics, Data Science, or related field; proficiency in statistical programmingDegree in Statistics, Mathematics, or related field; strong analytical skills
Work EnvironmentResearch-focused, developing models, advanced analyticsBusiness-focused, reporting, data visualization
Employer & Industry UsageTech companies, finance, healthcare, research institutionsRetail, marketing, finance, healthcare

Statistical Data Scientists focus on building complex models and advanced analytics, often requiring specialized statistical knowledge. Data Analysts primarily interpret data, create reports, and support decision-making with descriptive analytics. While both roles require strong analytical skills and familiarity with statistical tools, Statistical Data Scientists typically handle more complex modeling tasks and have a deeper focus on statistical theory.

What are popular job titles related to Statistical Data Scientist jobs in Toronto, ON? For Statistical Data Scientist jobs in Toronto, ON, the most frequently searched job titles are:
What job categories do people searching Statistical Data Scientist jobs in Toronto, ON look for? The top searched job categories for Statistical Data Scientist jobs in Toronto, ON are:
Statistical Data Scientist jobs near you
Data Scientist

Data Scientist

Stripe

Toronto, ON • On-site

Other

Posted 17 hours ago

Job description

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies-from the world's largest enterprises to the most ambitious startups-use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career.

About the teamOur 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 work is broad and varied, influencing how our products work (e.g. understanding user needs, preventing fraud, or optimizing charge flows), how our business works (forecasting key outcomes, managing liquidity, quantifying risk exposure), how our go-to-market motions operate (designing growth experiments, optimizing marketing investments, refining sales processes, and estimating causal effects), and everything in between. We have a variety of Data Science roles and teams across Stripe and will seek to align you to the most relevant team based on your background.What you'll do

We're looking for a variety of Data Scientists to partner with the Product, Finance, Payments, Security, Risk, Growth and Go-to-Market teams. You'll work closely with a specific part of the business, playing a crucial role in optimizing our systems and leveraging data to make strategic business decisions. As Data Scientists as Stripe, it's our mission to ensure that the company strategy, products, and user  interactions make smart use of our rich data, using  techniques like machine learning, statistical modeling, causal inference, optimization, experimentation, and all forms of analytics.

Who you are

We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum Requirements
  • PhD + 3 years, MS/MA + 6 years or BS/BA + 8 years of data science/quantitative modeling experience
  • Proficiency in SQL and a computing language such as Python or R 
  • Strong knowledge and hands-on experience in several  of the following areas: machine learning, statistics, optimization, product analytics, causal inference, and/or experimentation
  • Experience in working with cross-functional teams to deliver results
  • Ability to communicate results clearly and a focus on driving impact
  • A demonstrated ability to manage and deliver on multiple projects with a high attention to detail
  • Solid business acumen and experience in synthesizing complex analyses into actionable recommendations
  • A builder's mindset with a willingness to question assumptions and conventional wisdom
Preferred qualifications 
  • Experience deploying models in production and adjusting model thresholds to improve performance
  • Experience designing, running, and analyzing complex experiments or leveraging causal inference designs
  • Experience with distributed tools such as Spark, Hadoop, etc.
  • A PhD or MS in a quantitative field (e.g., Statistics, Engineering, Mathematics, Economics, Quantitative Finance, Sciences, Operations Research)

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