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Quant Jobs in Toronto, ON (NOW HIRING)

Bmo

VP, Portfolio Research

Toronto, ON · On-site

CA$96K - CA$180K/yr

Evaluate emerging datasets, quantitative methods, machine learning techniques, and research technologies; prioritize innovations that provide measurable investment or operational value.

Scotiabank

Manager, Model Validation

Toronto, ON · On-site

The Manager, Model Validation provides independent, objective assessment and effective challenge of quantitative models used across Treasury (ALM, liquidity and cashflow management, funds transfer ...

New

MUFG

Model Risk Management Analyst, AVP

Toronto, ON

The AVP, Model Validation Quantitative Analyst within the Quantitative Risk Control (QRC) supports best-practice model risk activities consistent with the MUFG Model Governance Program. The models ...

Robert Half

Insights Analyst

Toronto, ON · On-site

Support quantitative and qualitative research initiatives, including surveys, interviews, consultations, focus groups, benchmarking, environmental scans, literature reviews, and secondary research.

PwC

Digital Operations, Senior Associate

Toronto, ON · On-site

CA$84K - CA$134K/yr

Apply quantitative techniques withappropriate rigorbased on guidance from senior team members. Applied Modelling & Analysis * Build and support quantitative analysesincludingSupply chain network and ...

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Showing results 41-60

All JobsQuant JobsQuant Jobs in Toronto, ON

Quant information

See Toronto, ON salary details

$40.1K

$165.3K

$286.8K

How much do quant jobs pay per year?

As of Sep 4, 2026, the average yearly pay for quant in Toronto, ON is $165,343.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,678.00 and $188,959.00 per year, depending on experience, location, and employer.

What is a quant?

Quants, short for quantitative analysts, are professionals who use mathematical models, statistics, and computational techniques to analyze financial data and develop trading strategies. They are typically employed by investment banks, hedge funds, asset management firms, and financial technology companies. Quants play a crucial role in pricing securities, managing risk, and optimizing portfolios. Their expertise is essential for making data-driven decisions in complex financial markets.

What does a quant do?

Quant refers to a quantitative analyst whose responsibilities are to research and analyze market trends in finance. As a quant, you research and decipher statistics and design financial models to help banks, insurance companies, and other finance-focused organizations assess and prevent their risk, make sound investments, and better understand pricing structures to increase profit. Your duties also include creating codes for programs that follow financial trends and patterns, recording data and analyses, and consulting with business leaders in an organization to offer suggestions to combat potential financial risks. Large financial institutions and firms with trading processes typically hire quants.

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

To thrive as a Quant, you need strong quantitative and analytical skills, typically supported by advanced degrees in mathematics, statistics, physics, or related fields. Proficiency with programming languages like Python or C++, financial modeling, and familiarity with tools such as MATLAB or R are essential, along with knowledge of financial markets. Exceptional problem-solving, attention to detail, and effective communication help Quants stand out in collaborative and high-stakes environments. These skills enable Quants to develop robust models and strategies that drive critical decision-making and risk management in finance.

What are some common challenges faced by quants when collaborating with software developers and traders?

Quants often encounter challenges in bridging the gap between theoretical models and practical implementation. Effective communication is essential, as translating complex quantitative concepts into actionable trading strategies requires close collaboration with both software developers and traders. Misunderstandings can occur due to differences in technical language or priorities, so fostering a collaborative environment and being open to feedback is crucial. Regular meetings and clear documentation can help ensure that models are accurately implemented and aligned with trading objectives.

What is the difference between Quant vs Data Analyst?

AspectQuantData Analyst
Required CredentialsDegree in Math, Finance, or Computer Science; often requires advanced degreesBachelor's in Statistics, Economics, or related field; sometimes requires certifications
Work EnvironmentFinancial firms, hedge funds, investment banksCorporations, consulting firms, market research
Employer & Industry UsagePrimarily in finance and tradingAcross various industries including finance, marketing, healthcare
Common Search & Comparison IntentUnderstanding quantitative roles in financeExploring data analysis careers

While both Quant and Data Analyst roles involve working with data, Quants focus on developing complex models for trading and risk management in finance, often requiring advanced degrees and specialized skills. Data Analysts typically interpret data to inform business decisions across industries, with a broader scope and different tools. The roles overlap in data handling but differ significantly in application and industry focus.

Are quant jobs high paying?

Quant jobs, which involve quantitative analysis and modeling, are generally high paying within the finance industry due to the specialized skills required, such as programming, mathematics, and data analysis. Salaries can vary based on experience, location, and the firm, but they are often among the top-paying roles in finance and technology sectors.

What are the jobs in quant?

Quant jobs typically involve developing and implementing mathematical models to analyze financial data, manage risk, and inform trading strategies. Common roles include quantitative analyst, quantitative researcher, quantitative developer, and risk manager, often requiring strong skills in programming, statistics, and finance. These positions are prevalent in investment banks, hedge funds, and asset management firms.
More about Quant jobs

What are the most commonly searched types of Quant jobs in Toronto, ON?

The most popular types of Quant jobs in Toronto, ON are:

What are popular job titles related to Quant jobs in Toronto, ON?

For Quant jobs in Toronto, ON, the most frequently searched job titles are:

What job categories do people searching Quant jobs in Toronto, ON look for?

The top searched job categories for Quant jobs in Toronto, ON are:

Quant jobs near you
Infographic showing various Quant job openings in Toronto, ON as of August 2026, with employment types broken down into 96% Full Time, 1% Part Time, and 3% Contract. Highlights an 91% Physical, 3% Hybrid, and 6% Remote job distribution, with an average salary of $165,343 per year, or $79.5 per hour.

Python Developer - QIS (Indexes)

Jay Analytix

Toronto, ON • On-site

Full-time

Re-posted 22 days ago

Key responsibilities

  • Design, develop, and maintain Python-based applications supporting index calculation, rebalancing, and back-testing workflows

  • Implement and productionize systematic investment strategies in collaboration with quant researchers

  • Build and optimize data pipelines for market data ingestion, cleansing, and validation

Job description

Python Developer QIS (Indexes)

Location: Toronto, ON (Hybrid 3 days onsite per week) Experience: Minimum 8+ years Employment Type: Full-Time / Contract (as applicable)

About the Role

We are seeking a seasoned Python Developer with strong experience in Quantitative Investment Strategies (QIS) and index products to join our Toronto-based team. In this role, you will design, build, and maintain the technology platforms that power index calculation, rebalancing, and QIS strategy implementation. You will work closely with quantitative researchers, index analysts, and product teams to translate systematic strategies into robust, production-grade code.

Key Responsibilities
  • Design, develop, and maintain Python-based applications supporting QIS and index calculation, construction, rebalancing, and back-testing workflows
  • Implement and productionize systematic/rules-based investment strategies (e.g., factor, volatility, carry, momentum, multi-asset strategies) in collaboration with quant researchers
  • Build and optimize data pipelines for market data ingestion, cleansing, and validation across equities, fixed income, FX, commodities, and derivatives
  • Develop tools for index performance attribution, corporate action handling, and daily index level production
  • Ensure accuracy, auditability, and timeliness of index calculations and strategy outputs, including reconciliation and exception handling
  • Write clean, well-tested, well-documented code following software engineering best practices (version control, CI/CD, code reviews, unit/integration testing)
  • Improve performance and scalability of existing calculation engines and libraries
  • Collaborate with cross-functional stakeholders (research, product, operations, risk) to gather requirements and deliver solutions
  • Support production systems, troubleshoot issues, and participate in release and change management processes
  • Mentor junior developers and contribute to team standards and technical direction
Required Qualifications
  • 8+ years of professional software development experience, with strong hands-on expertise in Python
  • Proven experience in Quantitative Investment Strategies (QIS), index development/calculation, or systematic trading environments
  • Strong knowledge of financial markets and instruments equities, futures, options, FX, fixed income and index methodologies (rebalancing, weighting schemes, corporate actions)
  • Proficiency with Python scientific/data libraries: pandas, NumPy, SciPy; experience with back-testing frameworks a strong plus
  • Solid SQL skills and experience working with relational databases and large financial datasets
  • Experience with market data vendors and platforms (e.g., Bloomberg, Refinitiv/LSEG, FactSet)
  • Strong grasp of software engineering practices: Git, CI/CD pipelines, automated testing, code review, Agile delivery
  • Excellent analytical and problem-solving skills with high attention to detail and data accuracy
  • Strong communication skills and ability to work directly with quants, product, and business stakeholders
  • Bachelor's degree in Computer Science, Engineering, Mathematics, Finance, or a related quantitative field
Nice to Have
  • Master's degree or professional designation (CFA, FRM)
  • Experience at an index provider, investment bank QIS desk, asset manager, or ETF issuer
  • Exposure to cloud platforms (AWS, Azure, or GCP), containerization (Docker/Kubernetes), and workflow orchestration tools (e.g., Airflow)
  • Experience with performance optimization (vectorization, multiprocessing, Cython) for large-scale calculations
  • Familiarity with derivatives pricing, risk models, or portfolio optimization techniques
  • Knowledge of regulatory considerations for benchmarks/indexes (e.g., IOSCO principles, BMR)
Why Join Us
  • Work at the intersection of quantitative finance and technology on products used by institutional investors
  • Hybrid work model based in downtown Toronto
  • Collaborative environment with direct exposure to quant research and index product teams
  • Competitive compensation and benefits package