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Quantitative Modeling Jobs in Ontario (NOW HIRING)

Stripe

Data Scientist, Link

Toronto, ON · On-site

PhD with 3+ years, MS or MA with 6+ years, or BS or BA with 8+ years of data science or quantitative modeling experience * 3+ years in Product Analytics, Experimentation and Causal Inference

New

Scotiabank

Manager, PPNR Modeling

Toronto, ON · Hybrid

The role requires strong quantitative skills, programming capability, clear communication, and an ... Model Development: Work on statistical models to project PPNR (Pre-Provision Net Revenue) as a ...

Mackenzie Financial Corporation

Mackenzie Investments, founded in 1967, is a key part of IGM's business model, serving as a ... Educational background: degree in a field with experience using technology to solve quantitative ...

Posted today

Amazon

Applied Scientist, Sales AI

Toronto, ON

As an Applied Scientist on the team, you will bring deep expertise in quantitative modeling techniques such as Sequential Recommender Systems, Deep Learning, Reinforcement Learning or Hidden Markov ...

Amazon

Applied Scientist, Sales AI

Toronto, ON

As a part of our team, you will bring deep expertise in Generative AI and quantitative modeling (forecasting, recommender systems, reinforcement learning, causal inferencing or generative artificial ...

Amazon

Applied Scientist, Sales AI

Toronto, ON

... quantitative modeling techniques such as Sequential Recommender Systems, Deep Learning, Reinforcement Learning or Hidden Markov Models. You have the scientific and technical skills to build and ...

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Showing results 21-40

All JobsQuantitative Modeling JobsQuantitative Modeling Jobs in Ontario

Quantitative Modeling information

See Ontario salary details

$33K

$141.7K

$264K

How much do quantitative modeling jobs pay per year?

As of Aug 7, 2026, the average yearly pay for quantitative modeling in Ontario is $141,744.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,000.00 and $175,000.00 per year, depending on experience, location, and employer.

What are typical daily tasks and projects for someone in a quantitative modeling role?

In a Quantitative Modeling position, your daily activities usually include analyzing large datasets, building and validating predictive models, and developing algorithms to solve business or financial problems. You might spend time coding, running simulations, and interpreting model outputs to inform strategy or risk assessment. Collaboration is common—you'll often work with data scientists, business analysts, or subject matter experts to refine models and ensure they're aligned with organizational goals. The work is intellectually stimulating and fast-paced, with opportunities to see your analytical insights directly impact decision-making.

What is a quantitative modeling?

A Quantitative Modeling job involves using mathematical, statistical, and computational techniques to analyze data and construct models that help businesses make informed decisions. Professionals in this field work in finance, risk management, economics, and other industries to develop predictive models, optimize strategies, and assess uncertainties. They often use programming languages like Python, R, or MATLAB, along with machine learning and statistical methods, to solve complex problems.

What are the key skills and qualifications needed to thrive in the quantitative modeling position, and why are they important?

To excel in Quantitative Modeling, a strong foundation in mathematics, statistics, and data analysis is essential, often complemented by a degree in a quantitative field such as mathematics, finance, engineering, or physics. Proficiency in programming languages like Python, R, MATLAB, or statistical software, as well as familiarity with data visualization tools and financial modeling certifications (such as CFA or FRM), is highly valued. Effective quantitative modelers possess strong problem-solving abilities, attention to detail, and the ability to communicate complex findings clearly to both technical and non-technical stakeholders. These skills enable accurate, data-driven decision-making and the creation of robust predictive models in business, finance, or technology sectors.

What are popular job titles related to Quantitative Modeling jobs in Ontario? For Quantitative Modeling jobs in Ontario, the most frequently searched job titles are:
What job categories do people searching Quantitative Modeling jobs in Ontario look for? The top searched job categories for Quantitative Modeling jobs in Ontario are:
What cities in Ontario are hiring for Quantitative Modeling jobs? Cities in Ontario with the most Quantitative Modeling job openings:
Quantitative Modeling jobs near you
Infographic showing various Quantitative Modeling job openings in Ontario as of August 2026, with employment types broken down into 97% Full Time, and 3% Contract. Highlights an 81% In-person, 11% Hybrid, and 8% Remote job distribution, with an average salary of $141,744 per year, or $68.1 per hour.

Immediate Start - Quant Researcher - Systematic Commodities Hedge Fund

Moreton Capital Partners

Toronto, ON • On-site

Full-time

Medical, Life, PTO

Re-posted 18 days ago

Job description

Immediate Start - Quant Researcher – Systematic Commodities Hedge Fund

Moreton Capital Partners is rapidly expanding and seeking a talented Quantitative Researcher to join us in our Mexico City office to sit alongside a world class, international team.

This is a high-impact role from day one. You'll take full ownership of designing, testing, and refining the next generation of alpha signals in commodity futures, with your models feeding directly into live trading portfolios. Our research is grounded in advanced machine learning, robust testing frameworks, and deep expertise across global commodity markets.

We're looking for someone ready to hit the ground running and available to start immediately. In return, we offer a competitive salary, substantial performance share, comprehensive benefits, incredible work environment and a relocation package to make the move seamless.

Key Responsibilities
  • Research, prototype, and validate systematic trading signals across commodities using advanced ML methods.
  • Design and implement rigorous backtests with realistic frictions, walk-forward validation, and robust statistical tests.
  • Engineer and evaluate novel features from prices, fundamentals, positioning, options data, and alternative datasets (e.g., satellite, weather and global commodity cash pricing).
  • Blend multiple alpha forecasts into meta-models and portfolio signals, leveraging ensemble and Bayesian methods.
  • Develop portfolio construction and optimization techniques and analysis tools to be able to enhance performance and track effects on portfolio execution.
  • Collaborate with developers to transition research into production-ready strategies.
  • Monitor live performance, attribution, and model drift, ensuring continual improvement of the alpha library.

Requirements

  • Masters or PhD in either Statistics, Economics, Computer Science.
  • Strong background in machine learning and statistical modelling (tree-based models, regularization, time-series ML).
  • Proficiency in Python (pandas, NumPy, scikit-learn, XGboost, PyTorch/TensorFlow).
  • Understanding of time-series forecasting, cross-validation techniques, and avoiding look-ahead bias.
  • Academic experience in research and proven ability to translate academic work to production code.
  • Prior exposure to systematic trading or financial modelling.
  • Ability to design experiments, interpret results, and iterate quickly in a research environment.

Bonus points for:

  • Knowledge of commodities (agriculture, energy, metals) or macro markets.
  • Experience with feature engineering on non-traditional datasets (options positioning, weather, satellite).
  • Experience collaborating in version control environments.
  • Familiarity with portfolio optimization, risk parity, or Bayesian model averaging.
  • Publications, Kaggle competitions, or research track record demonstrating applied ML excellence.

Benefits

  • Direct impact: Your alphas will go live into production portfolios, with real capital behind them.
  • Research-first culture: We value deep thinking, novel approaches, and systematic rigor.
  • Close collaboration across a global team.
  • Career growth: Clear trajectory to senior researcher roles as we scale AUM and expand product lines.
  • Attractive compensation: Highly competitive base salary and annual bonus that scales as the business grows.
  • Relocation package to our Mexico City office, along with a competitive benefits offering that includes health and life insurance, a year-end bonus, and generous paid time off.
  • Positive, inclusive and encouraging work environment.