Senior Data Scientist

Quantum Technology Recruiting Inc. (QTR); Toronto; Hybrid; CAD 120,000 - 150,000; Full time

Job summary

Quantum Technology Recruiting Inc. (QTR) is seeking a Senior Data Scientist to join a client in a hybrid role based in Downtown Toronto.

The position focuses on advanced statistical modeling, machine learning, and large-scale data processing to support trading, risk management, regulatory reporting, and business decisions. The ideal candidate has 7+ years in data science, strong Python skills, and hands-on experience with PySpark and Azure Databricks, plus advanced SQL.

Qualifications

• Bachelor's or Master's degree in a relevant field.
• 7+ years of experience in Data Science, Machine Learning, or Advanced Analytics.
• 3+ years of Capital Markets/Financial Services experience.
• Strong programming skills in Python.
• Hands-on PySpark and Azure Databricks experience.
• Advanced SQL skills for large datasets.

Responsibilities

• Design, develop, validate, and deploy ML and predictive analytics models for Capital Markets use cases.
• Analyze large structured and unstructured datasets to identify trends, risks, and opportunities.
• Build scalable data pipelines and feature engineering workflows using Python, PySpark, and Azure Databricks.
• Develop statistical models supporting trading analytics, market risk, portfolio optimization, fraud detection, and regulatory reporting.
• Collaborate with traders, quantitative analysts, risk managers, business stakeholders, and tech teams to translate problems into analytical solutions.
• Optimize model performance through feature selection, hyperparameter tuning, validation, and monitoring.
• Develop reusable Python libraries and automate data science workflows using CI/CD and MLOps.

Skills

Python

Machine Learning

Data Analysis

Statistical Modeling

Education

Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Finance, or related discipline

Tools

PySpark

Azure Databricks

SQL

Job description

Position: Senior Data Scientist

Location: Hybrid 3-5 days in Downtown Toronto

Salary: $120K-$150K

Job Type: Permanent

Posting Type: Open vacancy

We are seeking a Senior Data Scientist to join our client to leverage advanced statistical modeling, machine learning, and large-scale data processing to develop innovative analytics solutions that support trading, risk management, regulatory reporting, and business decision-making.

Key Responsibilities

• Design, develop, validate, and deploy machine learning and predictive analytics models for Capital Markets use cases.
• Analyze large structured and unstructured datasets to identify trends, risks, anomalies, and business opportunities.
• Build scalable data pipelines and feature engineering workflows using Python, PySpark, and Azure Databricks.
• Develop statistical models supporting trading analytics, market risk, portfolio optimization, fraud detection, client analytics, and regulatory reporting.
• Collaborate with traders, quantitative analysts, risk managers, business stakeholders, and technology teams to translate business problems into analytical solutions.
• Optimize model performance through feature selection, hyperparameter tuning, validation, and monitoring.
• Develop reusable Python libraries and automate data science workflows using CI/CD and MLOps best practices.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Finance, or a related discipline.
• 7+ years of experience in Data Science, Machine Learning, or Advanced Analytics.
• 3+ years of experience within Capital Markets, Investment Banking, Asset Management, or Financial Services.
• Strong programming skills in Python.
• Hands-on experience with PySpark and Azure Databricks.
• Advanced SQL skills for querying and manipulating large datasets.

All applications are reviewed by our recruitment team, and hiring decisions are made by people. We may also use AI-enabled tools to support parts of the application review process.