Applied AI/ML Engagement Lead

Work Location:

Toronto, Ontario, Canada

Hours:

37.5

Line of Business:

Analytics, Insights, & Artificial Intelligence

Pay Details:

$108,800 - $163,200 CAD

This role is temporarily eligible for a pay premium above the posted salary range that is reassessed annually. You are encouraged to have an open dialogue with your recruiter who can provide more specific pay details for this role.

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.

Job Description:

We are seeking an experienced and business-savvy Analytics Engagement Lead to join our People Analytics team within AI2. This role sits at the intersection of data science, AI and Human Resources- and is critical to shaping how we use advanced analytics to drive business outcomes and improve employee experience.

In this high-impact role, you will partner directly with senior HR and business stakeholders to identify key opportunities where analytics can accelerate decision-making, unlock talent potential, and drive measurable business results. You'll act as both a strategic advisor and analytics translator, helping stakeholders turn complex challenges into data-driven solutions powered by predictive analytics, AI and machine learning.

You will collaborate closely with senior HR and business leaders to identify key workforce challenges, translate them into data-driven initiatives, and deliver actionable insights that balance business growth, regulatory compliance, and employee well-being.

KEY ACCOUNTABILITIES

• Provide expert knowledge in AI/ML, deep technical leadership and expertise to support and define future direction in one or more specialized AI/ML areas or lead strategic development efforts on new or emerging AI/ML related projects.

• Work closely with business owners as a trusted advisor to senior HR, risk, operations, and business leaders to identify opportunities and serve as an ambassador for AI/ML

• Play a lead role on cross functional teams of data and machine learning scientists, data and IT engineers, and business process owners to build cutting edge analytic solutions.

• Design and deliver analytics and AI insights into key HR programs (e.g., succession planning, DEI, attrition risk, skills forecasting).

• Develop powerful business insights from a broad range of data using advanced machine learning techniques to identify opportunities where people analytics can address business risks, improve efficiency, and drive workforce transformation.

• Translate business problems into people analytics projects and work by drawing on personal domain knowledge to help business leaders identify and prioritize their highest value business problems. Build strong relationships with partners to understand key stakeholder business problems, develop hypotheses for testing and interpret analytics with confidence

• Collaborate with data scientists to design solutions using predictive analytics, generative AI, NLP, and scenario modeling.

• Support responsible AI governance and compliance, ensuring alignment with internal risk and data privacy policies.

• Lead complex, cross-functional analytics initiatives from discovery to delivery, including change management and stakeholder adoption.

• Measure impact and drive continuous improvement using workforce KPIs.

• Synthesize technical findings into compelling stories tailored to executive audiences.

• Enable stakeholder self-service through dashboards and repeatable insight assets.

• Work with implementation experts to devise business-applicable plans to ensure that sophisticated analytics translate into impact at scale in an organization

• Ensure that what the data scientists are building is relevant to the business and its needs by bridging the technical expertise of data engineers and data scientists with the operational expertise of business leaders, managers and HR business partners

EXPERIENCE &