Tell us your story. Don't go unnoticed. Explain why you're a winning candidate. Think "TD" if you crave meaningful work and embrace change like we do. We are a trusted North American leader that cares about people and inspires them to grow and move forward.
Stay current and competitive. Carve out a career for yourself. Grow with us.
- Apply specialized skills and fundamental data science methods such as predictive modeling, time series forecast or deep learning, to build risk and return forecasting models used to manage equity portfolios. Ensure models are properly documented, tested and vetted as per regulatory and audit requirements.
- Participate in the management of TDAM’s Quantitative Equity mandates.
- Design, prototype, test and document enhancements to the existing forecasting models.
- Support the client portfolio management and relationship management teams for ad-hoc analysis.
- Continuously evaluate relevance of forecasting models and research for the current product mix and market conditions.
- Stay on top of economic and market conditions impacting the portfolios.
- Closely monitor and understand each strategy’s intended and unintended risks, and the underlying drivers of their P&L.
- Review, understand and vet changes in model preferences over time.
- Work closely with TDAM's data, quantitative research, portfolio management and risk management teams to evaluate and monitor the impact of various strategies.
- Coordinate with internal partners in the technology and business analyst teams to specify requirements for improvements to upstream systems needed by our team.
- Test and validate applications on the quantitative equity portfolio management system.
The ideal candidate will have the following:
- 5+ years of experience in Data science or quantitative research applied in finance
- Excellent theoretical knowledge and practical skills using machine learning algorithms, NLP, deep learning and statistics
- Programming proficiency in Python, MATLAB, R and related packages (Pandas, scikit-learn, Keras, TensorFlow, Theano etc.)
- Knowledge of writing queries to extract and transform data from a SQL server
- Strong data science, mathematics or statistics background, with practical knowledge of time series analysis, factor analysis, optimization theory and statistical learning theory
- Published research if any
- Graduate degree (Master or Ph.D.) in Data science, Statistics, Mathematics, Finance, Economics or a technical field such as Physics or Engineering
- CFA designation or working towards obtaining it
- Please note: This is a manager level role with a Market Title of VP, TDAM
At TD, we are committed to fostering an inclusive, accessible environment, where all employees and customers feel valued, respected and supported. We are dedicated to building a workforce that reflects the diversity of our customers and communities in which we live and serve. If you require an accommodation for the recruitment/interview process (including alternate formats of materials, or accessible meeting rooms or other accommodation), please let us know and we will work with you to meet your needs.
Job Category - Primary