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Data Scientist (VP & Director) - TD Asset Management - Job Opportunity at TD Bank

Toronto, Canada
Full-time
Executive
Posted: July 10, 2025
On-site
CAD 160,000-200,000 per year

Benefits

Comprehensive health and well-being benefits package providing medical, dental, and mental health coverage superior to many market competitors
Robust savings and retirement programs with employer matching contributions to support long-term financial security
Generous paid time off allocation including vacation, personal days, and sick leave exceeding industry standards
Banking benefits and discounts providing preferential rates and fee waivers on financial products
Professional development funding and career advancement programs including mentorship opportunities
Performance-based discretionary variable compensation awards recognizing individual and business achievements
Work-life balance initiatives supporting employee well-being and family needs

Key Responsibilities

Lead and scale a high-performance data science and engineering team, driving organizational capability development and talent retention in a competitive market
Establish strategic partnerships with portfolio managers, sales leadership, and C-suite executives to influence critical investment decisions through advanced ML tool deployment
Pioneer cross-functional AI initiatives that solve complex business challenges across multiple revenue streams, directly impacting firm profitability
Architect and deploy sophisticated machine learning solutions including Generative AI, predictive modeling, and deep learning systems that enhance investment decision-making processes
Design enterprise-scale data infrastructure and end-to-end pipelines supporting billions in assets under management
Mentor and develop technical talent while establishing AI/ML best practices and governance frameworks across the organization

Requirements

Education

Bachelor's or master's degree in computer science, Engineering, Data Science, or a related field

Experience

10+ years of commercial experience as in a data science role solving high impact business problems, including leading and maintaining high performance data science teams

Required Skills

Experience building, managing and mentoring high performance data science and engineering teams Proven track record of building and deploying AI applications, preferably in finance, investment banking, or related industries Strong background in machine learning, large language models (LLMs), agentic AI frameworks, and modern software engineering Theoretical and practical knowledge of machine learning, NLP (natural language processing), deep learning and statistics Extensive experience using Python including a strong grasp on machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas) Strong ability to prioritize and communicate to technical and non-technical audiences alike Strong software engineering skills: version control, CI/CD, testing, and code optimization Experience with data storytelling using Tableau, QlikView, Mode, Matplotlib, D3, or similar data visualization tools Knowledge of financial markets and experience using alternative datasets
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Sauge AI Market Intelligence

Industry Trends

The financial services industry is experiencing a massive transformation driven by AI and machine learning adoption, with asset management firms investing heavily in quantitative strategies and algorithmic trading capabilities to maintain competitive advantages in increasingly efficient markets. Generative AI and large language models are revolutionizing investment research and portfolio management, with firms racing to implement these technologies for alternative data analysis, risk assessment, and client communication automation. Regulatory compliance requirements are becoming increasingly complex, driving demand for sophisticated data science solutions that can ensure adherence while maintaining operational efficiency and profitability. The integration of ESG (Environmental, Social, and Governance) factors into investment decisions is creating new data requirements and analytical challenges that require advanced machine learning capabilities.

Salary Evaluation

The offered salary range of CAD 160,000-200,000 is competitive for the Toronto market, representing approximately USD 120,000-150,000. When combined with variable compensation, total package likely reaches CAD 250,000-300,000, positioning this role at the 75th percentile for similar positions in Canadian financial services.

Role Significance

Typically manages 8-15 direct reports including senior data scientists, ML engineers, and software developers, with indirect influence over 25-40 technical professionals across multiple business units within the asset management division.
This VP/Director level position represents a senior executive role with significant organizational influence, responsible for driving strategic AI initiatives across a multi-billion dollar asset management division. The role combines technical leadership with business strategy, requiring someone who can operate at the intersection of technology and finance.

Key Projects

Implementation of real-time portfolio optimization systems using advanced machine learning algorithms Development of alternative data integration platforms for enhanced investment research capabilities Creation of automated risk management systems incorporating ESG factors and regulatory compliance requirements Design of client-facing AI tools for personalized investment recommendations and reporting

Success Factors

Ability to translate complex technical concepts into business value propositions that resonate with portfolio managers and senior executives Strong track record of scaling data science teams while maintaining high performance standards and technical excellence Deep understanding of financial markets, investment strategies, and regulatory requirements specific to asset management Proven experience in implementing enterprise-scale AI solutions that directly impact revenue and risk management Exceptional communication skills to influence stakeholders across technical and business functions Strategic thinking capability to identify emerging opportunities in AI/ML that can provide competitive advantages

Market Demand

Extremely high demand exists for senior data science executives with financial services experience, as the combination of technical expertise, team leadership capabilities, and domain knowledge represents a scarce skill set in the Canadian market.

Important Skills

Critical Skills

Python and machine learning expertise are absolutely essential as the primary tools for implementing AI solutions in the financial services environment, with specific emphasis on TensorFlow and PyTorch for deep learning applications Team leadership and mentoring capabilities are crucial for scaling the data science function and attracting top talent in a competitive market Financial markets knowledge is critical for understanding the business context and ensuring that technical solutions align with investment objectives and regulatory requirements Communication skills are vital for influencing senior stakeholders and translating complex technical concepts into actionable business insights

Beneficial Skills

Strong software engineering practices including CI/CD and testing frameworks will enable the development of robust, production-ready AI systems Data visualization expertise will enhance the ability to communicate insights and build user-friendly interfaces for portfolio managers and clients Experience with alternative datasets will provide competitive advantages in identifying unique investment opportunities and risk factors Knowledge of regulatory frameworks will ensure compliance and facilitate faster implementation of AI solutions

Unique Aspects

Opportunity to work at the intersection of traditional asset management and cutting-edge AI technology within a stable, well-capitalized institution
Access to diverse datasets across retail banking, commercial lending, and investment management providing unique analytical opportunities
Involvement in strategic decisions affecting hundreds of billions in assets under management
Collaboration with portfolio managers who oversee some of Canada's largest pension funds and institutional accounts
Exposure to both Canadian and US markets through TD's cross-border operations

Career Growth

Career progression to C-suite roles typically occurs within 3-5 years for high-performing executives at this level, particularly given the accelerating demand for AI leadership in financial services.

Potential Next Roles

Chief Data Officer (CDO) positions at major financial institutions Head of Quantitative Research roles at hedge funds or investment banks Chief Technology Officer positions at fintech companies Senior Vice President of AI Strategy at global asset management firms

Company Overview

TD Bank

TD Bank Group is one of Canada's largest financial institutions and ranks among the top 10 banks in North America by assets. TD Asset Management manages over CAD 400 billion in assets and serves institutional clients, high-net-worth individuals, and retail investors across multiple investment strategies.

TD maintains a dominant position in the Canadian financial services market and has significant presence in the US Northeast corridor. The bank is recognized as a leader in digital banking innovation and has been consistently ranked among the world's safest banks.
This Toronto-based role positions the successful candidate at the heart of Canada's financial district, with opportunities to influence investment decisions across North American markets and interact with global institutional clients.
TD emphasizes a collaborative, client-focused culture with strong emphasis on diversity and inclusion. The organization invests heavily in employee development and maintains a reputation for work-life balance superior to many investment banking competitors.
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