Senior Data Scientist
Summary
Senior Data Scientist building ML and predictive analytics models for capital markets use cases—trading, risk, fraud detection, regulatory reporting—using Python, PySpark, and Azure Databricks in a hybrid Toronto role.
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.