ZipRecruiter

Log In

1

Phd In Mathematics Jobs in Toronto, ON (NOW HIRING)

Synechron

Quantitative Developer with MatLab

Toronto, ON · Hybrid

CA$130K - CA$140K/yr

Master of Mathematical Finance (MMF), PhD, or equivalent advanced degree in Financial Engineering, Applied Mathematics, or related fields. * Platform Experience:Hands-on experience with Databricks ...

Amd

CPU Performance Architect

Markham, ON

Adept at mathematical and statistical modeling * Detailed microarchitecture knowledge of a CPU, GPU ... Bachelors, Master's or PhD degree in Electronics/Computer Engineering or Computer Science with ...

Fusemachines

Lead Data Scientist

Toronto, ON · Remote

$110K - $140K/yr

Applicants should have a Masters, PhD, or advanced training in applied mathematics, engineering, computer science, or a similar related field. * 6+ years experience in Data Scientist or Machine ...

CookUnity

Director, Data Science/ML

Toronto, ON

PhD or Master's degree in Computer Science, Statistics, Mathematics, or related quantitative field * Experience with real-time ML systems and feature stores * Background in recommendation systems or ...

Hibernian General Insurance

Data Scientist

Toronto, ON · On-site

CA$80K - CA$120K/yr

MSc in Computer Science, Engineering, Mathematics, Statistics, Physics, or a related field (PhD preferred). * 2+ years of experience across the endtoend model development lifecycle, working with ...

Epistemix

Data Scientist

Toronto, ON · Remote

... in PhD program can count toward experience) * Masters or Ph.D in Data Science, Computer Science, Epidemiology, Economics, Public Health, Statistics, Mathematics, or similar quantitative field

CookUnity

Director, Data Science/ML

Toronto, ON · On-site

PhD or Master's degree in Computer Science, Statistics, Mathematics, or related quantitative field * Experience with real-time ML systems and feature stores * Background in recommendation systems or ...

previous page

Showing results 41-60

All JobsPhd In Mathematics JobsPhd In Mathematics Jobs in Toronto, ON

Phd In Mathematics information

What is a PhD in Mathematics?

A PhD in Mathematics is the highest academic degree in the field of mathematics, typically awarded after several years of original research and advanced coursework. The program involves the completion of a dissertation that contributes new knowledge to mathematical theory or application. Graduates are prepared for careers in academia, research, industry, and government, where they can apply their expertise to solve complex problems or teach at a university level.

Is a PhD in mathematics worth it?

A PhD in mathematics prepares individuals for careers in academia, research, data analysis, and quantitative roles, often requiring strong problem-solving and analytical skills. While it can lead to high-level positions, it typically involves several years of study and may have limited direct industry applications compared to other degrees, making its value dependent on career goals.

What is the salary of a PhD in mathematics?

The salary of a PhD in mathematics varies depending on the industry, experience, and location. Typically, mathematicians with a PhD working in academia, research, or industry can expect salaries ranging from $70,000 to over $120,000 annually. Higher salaries are common in private sector roles such as data science, finance, or technology companies that require advanced quantitative skills.

What types of collaborative opportunities are available for someone with a PhD in Mathematics within academic or industry settings?

Individuals with a PhD in Mathematics often collaborate with professionals from various disciplines, such as computer science, engineering, economics, or biology, depending on their area of expertise. In academia, this may involve joint research projects, interdisciplinary teaching, or grant applications with faculty from other departments. In industry, mathematicians frequently work on teams with data scientists, engineers, or analysts to solve complex problems, optimize processes, or develop new technologies. These collaborations not only broaden the impact of mathematical research but also provide valuable professional networking and learning opportunities.

Are math PhDs in demand?

Math PhDs are in demand in fields such as academia, data science, finance, and technology, where advanced analytical and problem-solving skills are valued. They often find opportunities in research, consulting, and roles requiring quantitative expertise, with employment prospects improving as data-driven decision-making grows across industries.

What is the difference between Phd In Mathematics vs Data Scientist?

AspectPhd In MathematicsData Scientist
Required CredentialsDoctorate in Mathematics or related fieldBachelor's or Master's in Math, Statistics, CS, or related field; PhD preferred
Work EnvironmentAcademic, research institutions, or R&D departmentsCorporate, tech companies, finance, healthcare
Industry UsageResearch, academia, governmentBusiness analytics, machine learning, data analysis
Common Search IntentAcademic careers, research rolesData analysis, machine learning roles

While a Phd in Mathematics focuses on advanced research and theoretical work, a Data Scientist applies mathematical and statistical skills to analyze data and solve business problems. Both roles require strong quantitative skills, but Data Scientists often work in industry settings with a focus on practical data applications.

What are the key skills and qualifications needed to thrive as a PhD in Mathematics, and why are they important?

To thrive as a PhD in Mathematics, you need advanced mathematical reasoning, problem-solving abilities, and a deep understanding of mathematical theory, usually supported by a strong academic background and research experience. Familiarity with mathematical software (such as MATLAB, Mathematica, or Python for computational work) and experience with academic publishing are commonly required. Strong analytical thinking, perseverance, and effective communication skills help you excel in research, teaching, and collaboration. These skills are crucial for pushing the boundaries of mathematical knowledge and successfully sharing insights with both academic and broader audiences.
What job categories do people searching Phd In Mathematics jobs in Toronto, ON look for? The top searched job categories for Phd In Mathematics jobs in Toronto, ON are:
Phd In Mathematics jobs near you
Infographic showing various Phd In Mathematics job openings in Toronto, ON as of August 2026, with employment types broken down into 73% Full Time, 24% Part Time, and 3% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution.

Data Scientist, Fraud

Stripe

Toronto, ON

Full-time

Posted 3 days ago

New

Job description

Who we areAbout 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 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

We're looking for a Data Scientist to join the Fraud Data Science team. In this role, you'll build and improve the models that power Stripe's fraud detection and loss management systems. You'll work closely with Fraud Engineering and Risk Operations to move models from research to production, and you'll use data to surface insights that shape fraud strategy across the business.

Data scientists on this team apply supervised and unsupervised machine learning, statistical modeling, causal inference, optimization, and experimentation to some of the most consequential risk problems in global payments.

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 with 1-3 years, MS or MA with 2-6 years, or BS or BA with 4-8 years of data science or quantitative modeling experience
  • Experience with Fraud, Risk or Financial Crimes
  • Proficiency in SQL and a computing language such as Python or R
  • 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
  • Strong business acumen and experience in synthesizing complex analyses into actionable recommendations
  • Proficiency with AI tools to accelerate model development, analysis, and coding
Preferred qualifications
  • Strong knowledge and hands-on experience in several of the following areas: machine learning, statistics, optimization, causal inference, and experimentation
  • Experience deploying models in production and adjusting model thresholds to improve performance
  • Experience designing, running, and analyzing complex experiments or leveraging causal inference designs
  • A builder's mindset with a willingness to question assumptions and conventional wisdom
  • 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)

Apply