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TD Model Validation (MV) group is responsible for the independent validation and approval of analytical models used for risk, pricing, hedging, insurance, marketing and capital evaluation for portfolio of financial products. This also includes validation of decision making models. Job Description
- The position reports to Senior Manager, Non-Retail Model Validation group within MV. Detailed accountabilities include:
- Validate (review and provide effective challenge) Machine Learning models and AI applications.
- Develop/implement Machine Learning model validation methodologies and standards. Ensure that the validation methodologies and standards are in line with industry best practice or address regulatory and audit requirements and/or findings in a timely manner.
- Develop and apply a variety of statistical tests and modeling techniques to identify/recommend improvements to models and undertake related initiatives. Ensure extensive testing of model sensitivity that help assessing model behavior and risk.
- Implement and evaluate external models used for benchmarking internal model performance. Participate in model selection and related due diligence activity.
- Actively participate with business partners in internal data management to ensure data integrity and the completeness of data capture for model validation and development purpose.
- Maintain full professional knowledge of techniques and developments in the field of Machine Learning and share knowledge with business partners and senior management.
- The position involves working effectively with different internal partners such as TD Wealth, TD Insurance, ED&A, PBSA, Layer6 and etc.
- Strong quantitative skills with an advanced degree in one or more of the following areas: computer science, mathematics, physics, statistics, machine learning, economics, finance, engineering, and/or actuarial science.
- Up to 3 years' experience of working in analytical environments.
- Experience with and strong knowledge of Machine Learning theory and predictive algorithms: Bagging and Gradient Boosting methods, Neural Networks/Deep Learning, NLP, Generalized Additive Models, Graphical Models, Bayesian/probabilistic methods and etc.
- Experience or knowledge of Machine Learning Model Interpretation/Explanation, as well as Bias/Fairness assessment, tools and algorithms.
- Experience with Big Data analytics tools and environments, such as, Hadoop/Hive, Spark, and H2O.
- Ability to research and implement Machine Learning algorithms from academic research papers is a plus.
- Obje ct Oriented programming skills.
- Proficient in one or more programming languages such as Java, Scala, Python and/or R.
- Knowledge of neural network tools such as Tensorflow/Keras, PyTorch and/or MXNet.
- Excellent verbal and written communication skills (position requires writing reports).
- Quick learner who constantly works on improving their skills and expertise.
- Good time management and multitasking skills with minimal supervision.
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.