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TD Bank · Toronto, Canada
Work Location: Toronto, Ontario, Canada Hours: 37.5 Line of Business: Analytics, Insights, & Artificial Intelligence Pay Details: $96,900 - $136,800 CAD 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: The Manager, Data Science leads a specialized team of data professionals varying in size and complexity that are responsible for aiding to drive changes and improvement in business practices through data science. This role manages the overall data scientist team or function for a key business which may include Modelers and/or Data Scientist roles. This role may also oversee the development of data models, data mining and analytic solutions. Day to day: Lead and mentor a team of Data Scientists, providing technical guidance, coaching, performance feedback, and career development support. Partner with business stakeholders to identify, prioritize, and deliver machine learning, AI, and advanced analytics use cases. Translate business requirements into analytical frameworks, machine learning models, and actionable recommendations. Develop, test, and deploy predictive, prescriptive, and generative AI solutions to address business challenges. Oversee model development activities including feature engineering, algorithm selection, model training, validation, and performance monitoring. Work closely with data engineers and technology teams to ensure scalable, production-ready solutions. Conduct exploratory data analysis and communicate findings to both technical and non-technical audiences. Support proof-of-concepts, pilot programs, and experimentation initiatives to evaluate new AI and machine learning capabilities. Ensure model governance, documentation, validation, and monitoring requirements are met in accordance with enterprise standards. Evaluate emerging data science techniques, AI te