Applied Machine Learning Scientist II (US)

Work Location:

Charlotte, North Carolina, United States of America

Hours:

40

Pay Details:

$96,130 - $155,950 USD

TD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience at TD. Our compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The base pay actually offered may vary based upon the candidate's skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs.

As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.

Line of Business:

Analytics, Insights, & Artificial Intelligence

Job Description:

Why Work with Us?

At TD Bank US Compliance, we're on a mission to build a more resilient and scalable compliance risk management function. As part of our team, you'll play a key role in reshaping compliance structures and processes, driving innovation at every level. Here, each team member has a chance to make a tangible impact – both in day-to-day operations and in the design of a future-focused compliance program. This not just about implementing a new program – it's about creating a culture of compliance that will cascade throughout the organization.

As the backbone of our financial system, financial institutions have rich large-scale datasets and are rapidly adopting models to improve customer experience and drive business performance, including AI and machine learning. While models are increasingly pervasive across society, many outstanding questions and challenges must be answered to ensure that model outcomes are fair and transparent. In this position, you will play a key role in ensuring the appropriate application of models and positioning TD as an industry leader in Responsible and Ethical AI.

This role focuses on the intersection of fairness, transparency, and accountability in Artificial Intelligence and Machine Learning (AI/ML). The successful candidate will contribute to ensuring that models are developed and deployed responsibly, with outcomes that are explainable, trustworthy, and aligned with ethical standards. Financial institutions rely on large-scale datasets and advanced analytics to enhance customer experience and business performance, making rigorous oversight essential. In this position, you will play a key role in evaluating models, addressing emerging challenges related to responsible AI, and supporting the appropriate application of analytical solutions while helping position the organization as a leader in ethical and compliant AI practices.

TEAM DESCRIPTION

The successful candidate will join the Fair Banking Compliance Model Review team, which is responsible for ensuring the bank’s models are fair, transparent, and responsibly deployed. This role requires strong expertise in Generative AI and machine learning, advanced data analysis, and the selection of appropriate statistical tests and bias metrics, as well as familiarity with emerging fairness methodologies. The incumbent will evaluate existing fairness approaches and contribute to the design and evolution of the bank’s fairness evaluation framework. This is a senior role requiring deep analytical judgment, strong stakeholder management, and effective communication skills, and it plays a critical part in providing independent oversight of models to support fair banking compliance. The role may include people management responsibilities.

Key Responsibilities:

• Lead reviews of machine learning, AI, and Generative AI models across TD to identify potential fairness and bias risks.

• Represent Compliance in major projects, initiatives, and enterprise engagements.

• Perform quantitative analyses to identify fair lending risks associated with model development and use.

• Identify and recommend alternative approaches to mitigate fair lending bias arising from models.

• Develop specialized analytical tools to support project-specific needs or ongoing review activities.

• Compile, analyze, and generate ad-hoc analytical reports for internal stakeholders.

• Lead research efforts by applying advanced statistical analysis and modeling expertise.

• Provide advisory support to line-of-business model owners on compliance best practices aligned with internal policies and industry standards.

• Lead cross-functional teams or initiatives involving significant complexity.

• Independently manage end-to-end functional programs and deliverables.

• Apply sound judgment and a sophisticated analytical mindset to identify risks and recommend solutions.

• Communicate complex analytical findings clearly to non-technical audiences.

• Operate autonomously as a subject matter expert while mentoring and guiding others within the area of