Data Scientist II

Job description

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Department Overview

The Global Compliance Department mission is to foster a culture of integrity, ethics and compliance and deliver independent risk management and oversight of regulatory compliance risk and conduct risk throughout TD. This is performed in accordance with the Global Compliance Department Mandate, in execution of the Global Compliance Operating Framework (GCOF). The department achieves this by independently assessing the adequacy of, adherence to and effectiveness of regulatory compliance management programs and controls in the business; delivering objective guidance and independent challenge; proactively managing regulatory change; and providing trusted and reliable reporting, advice and opinion to senior leadership and the Board on the state of regulatory compliance risks, controls and outcomes.

Job Description

About this Role

Do you want to dive into the intersection of fairness and machine learning? Do you want to tackle how we can leverage explainability approaches to open machine learning and AI black boxes for customers? Are you passionate about technology and ethics? If so, then this is a job for you.
As the backbone of our financial system, banks have rich large-scale datasets and are rapidly adopting machine learning solutions to improve customer experience and drive business performance. While machine learning is increasingly pervasive across society, there are many outstanding questions and challenges to ensure that ML/AI solutions are fair and transparent. In this position, you will play a key role in ensuring the ethical application of machine learning.

This position reports to the Senior Manager of the Compliance Oversight of Models Office. Detailed accountabilities include:
  • Conduct research on how to identify, assess, and address ML modeling risks and associated concerns, especially fairness and explainability
  • Evaluate ML model development procedures and processes for model compliance risks (e.g., unfairness)
  • Support the development of technical standards and guidelines covering model risk matters, and draft key Compliance documents in appropriate coordination with stakeholders
  • Maintain up-to-date knowledge of techniques and developments in the field of machine learning and share knowledge with business partners and senior management
  • Lead compliance review of machine learning use cases across TD, and build a close working relationship with business units across the Enterprise. Objectives include:
    • Supporting compliance risk management associated with models used by TD;
    • Supporting the business in identifying models whose outcomes impact customers or communities;
    • Assessing models for regulatory compliance and conduct risk, including fair banking risk; and
    • Supporting the business in monitoring regulatory compliance and removing or mitigating conduct risk throughout the model lifecycles.

  • Partner with Legal, Privacy, Model Validation and other Compliance Units
  • Represent Compliance in projects that have a regulatory compliance component and/or carry regulatory risk exposure related to the use of a model

The position involves working effectively with different internal partners such as TD Wealth, TD Insurance, ED&A, PBDA, and Layer 6 among others.


The successful candidate will join the Compliance Oversight of Models Office (COMO), an interdisciplinary team that sits at the intersection of data science, regulatory understanding, and ethics. COMO is responsible for the global compliance oversight of models from a regulatory compliance and conduct risk perspective. COMO's oversight spans the model lifecycle and engagement with disparate model stakeholders. The COMO mandate includes but is not limited to:
  • Assessing models for regulatory compliance and conduct risk;
  • Providing oversight and independent challenge to approaches used to identify, assess, and address model compliance risks and concerns (e.g., fairness/bias and explainability); and
  • Supporting the business in monitoring regulatory compliance and removing or mitigating conduct risk throughout the model lifecycle.

COMO embraces a multidisciplinary approach, celebrating the alternative, multi-faceted perspectives needed to ensure that AI is developed and deployed ethically. COMO is committed to helping team members develop professionally and expand their horizons because the best way to address the ML challenges of tomorrow is to have a team that can see those challenges today.

Job Requirements
What can you bring to TD? Tell us about your most relevant experience, credentials and knowledge for this role, as well as these essential requirements and attributes:
  • Hands-on data science expertise including, but not limited to, machine learning, statistics, and data visualization
  • Experience with/knowledge of methods, techniques and tools to support explainable AI (XAI) and address ML bias/fairness
  • The ability to stay abreast of developments in artificial intelligence and machine learning and provide thought leadership the same
  • The ability to effectively collaborate with technical and non-technical stakeholders across the model development lifecycle and as part of enterprise initiatives
  • Ability to influence people and deal with conflicting points of view and to effect creative and responsive solutions
  • Excellent verbal and written communication skills
  • Comfort representing Compliance in executive-level initiatives and meetings, and working with all levels of staff within the Enterprise
  • Work effectively as a team to peer review other team members' work and share knowledge
  • Assist with response to regulatory inquiries, examinations and investigations as applicable.
  • Represent Compliance in projects that have a regulatory compliance component and/or carry regulatory risk exposure.
  • Quick learner who constantly works on improving skills and expertise.
  • Good time management and multitasking skills with minimal supervision.

  • PhD (preferably in computer science, math, statistics, engineering, or related quantitative field)
  • Relevant experience with the machine learning model development lifecycle (model validation expertise would be especially advantageous)
  • Demonstrable engagement with the issues of explainability and/or fairness in the context of advanced analytics and machine learning

Additional Information


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.

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