Applied Machine Learning Scientist II (US)

TD Bank • Greenville, NY

4h

About The Position

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.
The Applied Machine Learning Scientist II is responsible for providing technical knowledge and expertise on advanced analytics and machine learning across a broad range of analytics functions including data and modelling frameworks, tools, technology, processes and procedures. This role generally provides expertise in stakeholder interactions related to complex advanced analytics related material. Additionally, this role plays a lead role in the development of AI/ML systems to solve a range of complex problems and is adept at translating business objectives into technical solutions.

Requirements

• Undergraduate degree required, advanced technical degree preferred (e.g., math, physics, engineering, finance or computer science)
• Graduate's degree preferred with either progressive project work experience, or;
• 1+ years relevant experience (includes post graduate experience)
• Adept at technical project execution, strategic planning and effective communication.
• Accountable for specialized knowledge in a field of AI/ML
• Works autonomously and accountable for acting as a lead within a function
• Undertakes and completes a variety of complex initiatives requiring seasoned specialist AI/ML knowledge and/or the integration of cross functional processes
• Typically deals with senior/executive management

Nice To Haves

• Master's degree in computer science, machine learning, AI, engineering, statistics, data science, mathematics or related field with 4+ years of relevant work experience in either developing or validating Generative AI, LLMs, NLP and other Deep Learning models.
• PHD with specialization in ML, AI, or Statistics is a plus.
• In-depth knowledge of AI/ML methodologies, concepts and theory including Generative AI, Deep Learning, modern Natural Language Processing (NLP), Retrieval-Augmented Generation (RAG), Transformers, Diffusion models etc.
• Experience with Deep Learning and Generative AI technology stacks and libraries such as PyTorch, PromptFlow, LangChain, HuggingFace, etc.
• Motivated to stay up to date with the latest advancements in Generative AI, machine learning, and cloud technologies.
• Academic or industry research experience in Responsible AI, fairness, or model evaluation
• Proficient in one or more scripting/programming languages such as Python.
• Familiarity with cloud platforms (e.g., Azure, AWS) and big data technologies (e.g., PySpark, Hadoop).
• Knowledge of machine learning explain-ability/interpretability algorithms.
• Excellent verbal and written communication skills and stakeholder management abilities (position requires writing and reviewing reports of a technical nature).
• Strong critical and analytic thinking skills.
• Excellent time / project management and multitasking skills with minimal supervision.
• Ability to work independently and collaboratively in a fast-paced, dynamic environment.
• Publications in relevant conference and journals and research in GenAI/LLM field is a plus.
• Ability to implement AI/ML algorithms from academic research papers is a plus.

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 expertise.
• Manage multiple concurrent projects and priorities in a dynamic business environment.
• Lead and mentor junior team members.

Benefits

• Our Total Rewards package reflects the investments we make in our colleagues to help them and their families achieve their financial, physical and mental well-being goals.
• Total Rewards at TD includes base salary and variable compensation/incentive awards (e.g., eligibility for cash and/or equity incentive awards, generally through participation in an incentive plan) and several other key plans such as health and well-being benefits, savings and retirement programs, paid time off (including Vacation PTO, Flex PTO, and Holiday PTO), banking benefits and discounts, career development, and reward and recognition.
• Through regular development conversations, training programs, and a competitive benefits plan, we’re committed to providing the support our colleagues need to thrive both at work and at home.
• You’ll have regular career, development, and performance conversations with your manager, as well as access to an online learning platform and a variety of mentoring programs to help you unlock future opportunities.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level