Senior Data Scientist
Design and deploy machine learning models and scalable data pipelines to support trading, risk management, and regulatory reporting. Collaborate with stakeholders to translate complex business problems into analytical solutions for Capital Markets.
- Hybrid
- Toronto, ON
- Posted Aug 10, 2026
- Apply by Sep 9, 2026
- 1 position
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Job summary
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. Interested? Please send your resume in Word format to Neeta Bernard at [email protected]. REFER A NEW HIRE AND EARN A CASH BONUS! For details, click here. 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.
What you’ll do
Design and deploy machine learning models and scalable data pipelines to support trading, risk management, and regulatory reporting. Collaborate with stakeholders to translate complex business problems into analytical solutions for Capital Markets.
Requirements
Requires a degree in a quantitative field and over 7 years of experience in Data Science, with at least 3 years specifically in financial services. Proficiency in Python, PySpark, Azure Databricks, and advanced SQL is essential.
Listed skills
- SQLPreferred
- CI/CDPreferred
- Machine learningPreferred
- PythonPreferred
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Statistical Modeling
- Machine Learning
- Python
- PySpark
- Azure Databricks
- SQL
- Predictive Analytics
- Feature Engineering
- MLOps
- CI/CD
- Data Pipelines
- Capital Markets Analytics
Job areas
- Data & Analytics
- Finance & Accounting
- Technology
- Science & Research
- Software
Additional details
- Minimum education
- Bachelor’s degree
- Minimum experience
- 7+ years
- Apply by
- Sep 9, 2026
- Posting language
- English
- Working hours
- 40 hours per week
- Office presence
- 3 days per week
- Seniority
- Associate