Computer Science Td Jobs (NOW HIRING)

Work Location:

Hours:

Pay Details:

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:

Job Description:

The Senior 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:

The Senior Manager, Data Science will deliver measurable value through predictive, prescriptive, and generative AI capabilities. The successful candidate will combine deep technical expertise with strong leadership skills to build high-performing teams and establish a culture of innovation, experimentation, and responsible AI.

• Lead and develop a team of Data Scientists, providing coaching, mentorship, technical guidance, and career development.
• Partner with business leaders to identify and prioritize high-value machine learning, artificial intelligence, and advanced analytics opportunities.
• Translate complex business problems into analytical frameworks, models, and actionable insights.
• Oversee the end-to-end data science lifecycle, including problem formulation, feature engineering, model development, validation, deployment, monitoring, and ongoing optimization.
• Guide the development of predictive, prescriptive, and generative AI solutions that improve business performance, efficiency, customer experience, and risk management outcomes.
• Collaborate with data engineering, technology, and platform teams to ensure scalable and production-ready solutions.
• Establish model governance, validation, explainability, documentation, and monitoring practices in accordance with enterprise risk management standards.
• Evaluate emerging AI, machine learning, and data science techniques and recommend practical applications across the organization.
• Present analytical findings, recommendations, and business cases to senior executives and stakeholders in a clear and impactful manner.
• Drive experimentation and innovation through proof-of-concepts, pilots, and test-and-learn initiatives.
• Ensure responsible and ethical use of AI through adherence to regulatory requirements, governance frameworks, and internal policies.
• Manage portfolio planning, resource allocation, and delivery execution across multiple concurrent data science initiatives.

Depth & Scope:

• Provides people management leadership by hiring the best talent, setting goals, developing staff, managing employee performance and compensation decisions, promoting teamwork and handling any/all disciplinary actions, as required
• Oversees and leads a large and/or highly complex and diverse analytical function for an area of significant risk, complexity or scope
• Strategic partner to leadership team on the management of the portfolio and financials, with deep industry, external/internal, enterprise knowledge, recognizing and anticipating emerging trends and identifying operational efficiencies and opportunities with other business management/enterprise areas
• Facilitates key strategic discussions and provides thought leadership to executive audience (output may include strategic roadmap and/or deliverables/frameworks/short to long term goals etc.)
• Sets operational team direction and collaborates with others to execute on common goals
• Focuses on longer range planning for functional area (e.g. 12 months or greater)

Education & Experience:

• Undergraduate degree or advanced technical degree preferred (e.g., math, physics, engineering, finance or computer science) Graduate's degree preferred with either progressive project work experience, or;
• 7+ year of relevant experience; higher degree education and research tenure can be counted

Customer Accountabilities:

• Leads team of Data Scientists and provides day-to-day direction as needed
• Acts as People Manager and is responsible for ongoing coaching and development, setting objectives, assessing performance
• Works closely with business owners to identify opportunities and serves as an ambassador for data science
• Leads and oversees the design and delivery of enterprise analytic solutions for customers
• Works in a highly interactive, team-oriented environment with Big Data developers, and analytical experts
• Collaborates with business partners to shape and prioritize ad hoc analysis

Shareholder Accountabilities:

• Provides analytical thought leadership and stays current on developments in data mining and the application of data science
• Manages workload of data science team, assigning data request to staff based on skills and development needs
• Supports execution with excellence on key initiatives/programs
• Designs effective test and learns for various programs or scenarios
• Develops business specific plans; ensures work and resources are aligned to support objectives
• Identifies opportunities for business growth within a specific business or function by identifying potential use cases and value drivers
• Proactively supports the identification of issues, trends and opportunities, and brings forward recommendations based on judgment and facts
• Leads team to prepare framework to succinctly take complex data and translate it into clear and concise recommendations
• Ensures deep understanding and contributes to the achievement of the business strategy, goals, and objectives
• Ensures team adheres to enterprise frameworks and methodologies related to overall business management activities
• Leads relationships with corporate and/or control functions to ensure alignment with enterprise and/or regulatory requirements
• Supports team in staying knowledgeable on emerging issues, trends and evolving regulatory requirements and assesses potential impacts to the Bank
• Assesses/identifies key issues and escalates to appropriate levels and relevant stakeholders and business management where required
• Identifies, mitigates, and reports on risk issues per enterprise policy/guidance and ensures appropriate escalation processes are followed
• Ensures business operations are following applicable internal and external requirements (e.g. financial controls, segregation of duties, transaction approvals and physical control of assets)
• Leads relationships with business lines / corporate and/or control functions to ensure alignment with enterprise and/or regulatory requirements
• Leads or contributes to cross-functional/enterprise initiatives as an organizational or subject matter expert helping to identify risk/provide guidance for complex situations
• Protects the interests of the organization - identifies and manages risks, and escalates non-standard, high-risk transactions/activities as necessary
• Manages oversight process, risk-based identification and monitoring of related risks and regulatory compliance across the supported functions, while ensuring key controls and processes are effectively managed
• Oversees or leads the facilitation and/or implementation of action/remediation plans to address performance/risk/governance issues
• Keeps abreast of emerging issues, trends, and evolving regulatory requirements and assesses potential impacts
• Maintains a culture of risk management and control, supported by effective processes in alignment with risk appetite

Employee/Team Accountabilities:

• Cultivates and models the Colleague Promise to support colleague growth, and a culture of care; makes an impact at work and in our communities by leading with authenticity and supporting well-being to represent TD's brand
• Connects the alignment of colleague's contributions with the TD Shared Commitments
• Builds and retains an engaged and diverse team that embraces diversity of thought, creativity and curiosity; where every colleague and customer are valued, respected, and listened to; committed to a common goal and collaborates to move with speed and get things done
• Demonstrates inclusive leadership by taking meaningful action with intention to support colleagues and customers across all dimensions of diversity, including those from underrepresented communities, being actively anti-racist, attracting and retaining diverse slate of candidates, nurturing mutual respect, inclusivity of thought and collaboration to drive successful results
• Sustains, identifies strong talent, recruits and develops a diverse talent pipeline of qualified workforce to innovate and maximize individual strengths to lead to a better business outcome
• Enables colleague growth by encouraging colleague development to achieve career and business objectives, ensuring timely feedback, motivating appreciation and recognition to all colleagues
• Enables a continuous learning culture by proactively seeking, listening to and actioning feedback from peers and from colleague listening opportunities to continuously improve the colleague experience and grow your personal leadership
• Fosters an environment that promotes sharing of knowledge, information, skills, and subject matter expertise among the team; ensures timely management and escalation of issues and creates opportunities to collaborate with other functions and team
• Leads team through change and creates an environment where teams feel psychologically safe to challenge current practices by modeling resiliency and flexibility, communicating a compelling vision with clarity and empowering colleagues to drive innovation
• Contributes to the development of business segment and/or enterprise functional strategic priorities within their operational area or field of specialty that drive results
• Develops annual and/or long-term plans for own area that are aligned with enterprise-wide priorities, reinforces a focus on results that align to One TD
• Fosters a high-performance culture by setting team targets and objectives, promotes and facilitates on-going feedback/coaching and conducting Quarterly Check-Ins for all colleagues to drive accountability and business results
• Manages employees in compliance with all human resources policies, procedures and guidelines of conduct

Preferred Qualifications:

• "Big Tech" experience strongly preferred
• Master's degree in data science, PhD in data science, Computer Science, Machine Learning, Statistics, Applied Mathematics, Physics, Engineering, or a related quantitative field.
• 3+ years deep expertise in machine learning algorithms, statistical modeling, predictive analytics, and experimentation methodologies.
• 7+ years of experience applying advanced analytics, machine learning, artificial intelligence, or statistical modeling techniques in complex business environments.
• Advanced proficiency in Python and common data science libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, XGBoost, or similar frameworks.
• Experience developing and deploying Generative AI, Large Language Model (LLM), Retrieval-Augmented Generation (RAG), or Agentic AI solutions.
• Experience operationalizing machine learning models within enterprise environments using MLOps practices and cloud platforms.
• Strong understanding of model governance, explainability, fairness, bias mitigation, and responsible AI practices.
• Experience leading cross-functional AI and analytics initiatives involving business, technology, risk, and governance stakeholders.
• Demonstrated ability to communicate complex analytical concepts to executive and non-technical audiences.
• Experience in financial services, banking, risk management, audit, regulatory, or highly regulated industries.
• Familiarity with cloud-based analytics environments such as Azure, AWS, or Google Cloud.
• Experience managing a portfolio of data science initiatives and delivering measurable business value.

Physical Requirements:

Never: 0%; Occasional: 1-33%; Frequent: 34-66%; Continuous: 67-100%

• Domestic Travel - Occasional
• International Travel - Never
• Performing sedentary work - Continuous
• Performing multiple tasks - Continuous
• Operating standard office equipment - Continuous
• Responding quickly to sounds - Occasional
• Sitting - Continuous
• Standing - Occasional
• Walking - Occasional
• Moving safely in confined spaces - Occasional
• Lifting/Carrying (under 25 lbs.) - Occasional
• Lifting/Carrying (over 25 lbs.) - Never
• Squatting - Occasional
• Bending - Occasional
• Kneeling - Never
• Crawling - Never
• Climbing - Never
• Reaching overhead - Never
• Reaching forward - Occasional
• Pushing - Never
• Pulling - Never
• Twisting - Never
• Concentrating for long periods of time - Continuous
• Applying common sense to deal with problems involving standardized situations - Continuous
• Reading, writing and comprehending instructions - Continuous
• Adding, subtracting, multiplying and dividing - Continuous

The above statements are intended to describe the general nature and level of work being performed by people assigned to this job. They are not intended to be an exhaustive list of all responsibilities, duties and skills required. The listed or specified responsibilities & duties are consi...