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Market Risk and Model Development (MRMD) organization is responsible for modeling, analyzing, reporting and monitoring all aspects of risks associated with the bank's businesses, including: trading and non-trading market and credit risk, operational risk and liquidity risk in accordance with TD's risk appetite and regulatory expectations. MRMD supports the TD's retail lending business, commercial and wholesale lending business - in both Canada and US, our capital markets business (TD Securities) as well as Treasury and Balance Sheet Management (TBSM).
The Model Development team is responsible for developing and maintaining models that are used in a wide variety of applications to measure risk and adjudicate credit for all Canadian retail and non-retail lending portfolios, as well as quantify operational and market risk metrics. Some of the models are used by risk management to make decisions such as adjudication, monitor accounts and portfolios risk, as well as to define and execute risk management strategies. Other models also produce estimates of expected losses and cash flow shortfalls under various economic scenarios to calculate Risk Weighted Assets (RWA), Allowances for Expected Credit Losses (ECL), and views of the Bank's balance sheet and financial statements under downturn economic scenarios for Stress Testing exercises such as the internal Enterprise Wide Stress Test (EWST) and regulatory stress tests such as OSFI's Macro-economic Stress Test (MST) and the Fed's Comprehensive Capital Adequacy Requirements (CCAR).
This role sits in the newly formed MD Innovation team with specific mandate to research, develop and implement innovative approaches to risk modeling, measurement and analytics using advanced analytics, modern data science, machine learning and automation tools across MRMD.. The Innovation team is also exploring identified opportunities to automate certain processes across teams in MRMD that currently involve significant manual efforts. The team is also thinking of innovative ways to make these processes more efficient.
You will have the opportunity to work with very highly-skilled quants and experienced risk professionals across teams in MRMD including: MD, Capital Markets Risk Management (CMRM) and Market Risk Control (MRC) as well as stakeholders from other Risk, business and technology areas in the organization.
Reporting to the Senior Manager, Advanced Analytics and Innovation in the Model Development group, you will:
Research, develop, implement and facilitate end-to-end machine learning solutions related to risk and capital modeling, by:
Collaborating actively with other members of the Innovation team, Model Development group, other Risk areas, Enterprise Data & Analytics and IT;
Sourcing data from various systems across the bank;
Building efficient and scalable data pipelines from databases both from within and outside the Hadoop environment;
Performing data cleansing, data wrangling and feature engineering;
Training and testing alternative machine learning algorithms to select the best candidate model;
Working with Enterprise Data & Analytics and IT to deliver models and communicate results and insights to model owners/users;
Producing comprehensive model documentation, including presentations to various stakeholders;
Monitoring model performance for drift in performance;
Working closely with other aspects of the model lifecycle, such as engaging with Model Validation and Model Risk Management, as required.
Leverage your superior coding, problem solving and analytical skills to simplify and selectively automate processes and workflows in collaboration with teams across MRMD. This will involve, but will not be limited to, the following:
Business & technical requirements gathering and analysis;
Design of solutions;
Coding and development in Python in compliance with standard software development practices and lifecycle (SDLC), TD's ED&A guidelines and other risk-related guidelines;
Testing, maintenance and user support for codes and tools developed.
Be involved in other risk and capital modeling projects in other areas of the Model Development group, as the need arises.
Stay current on advances in data science and machine learning and the application to risk modeling.
Graduate degree in a quantitative field (e.g. statistics, mathematics, data/computer science, machine learning, econometrics, etc.).
3+ years' experience building and implementing modern data science / machine learning models is required.
3+ years' experience working in a Hadoop environment (HDFS, Hive, Spark, etc.) and writing SQL-type database queries.
Some cloud (AWS, Azure, etc.) experience.
Advanced coding skills in Python or R and experience working with the standard open source machine learning packages in Python and R, such as Scikit-learn, TensorFlow, Keras, Caret, etc.
Experience using Python to consume APIs.
Experience with version control tools (Git/Bitbucket).
An experienced data scientist who has been involved along the entire data science lifecycle (e.g.: TDSP) - desirable but not required.
Some experience in risk modeling, quantitative finance, capital markets/market risk, banking, etc. - strongly preferred.
Strong communication skills - both oral and written.
A curious self-starter with strong attention to detail, an owner's mindset who is able to produce top quality work with limited direction but also work very well as part of a team.
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.