Data Scientist III
About The Position
Data Scientist III – Wealth AI2 (Advice Journey, Solutions & Enablement) Analytics Engagement Lead. Wealth AI2 (Anaytics, Insights & AI) builds data, analytics and reporting capabilities that help TD Wealth teams make better, faster decisions by delivering trusted insights and scalable analytics solutions that drive value. This role sits within the Wealth AI2 team, supporting the Wealth Advice Solutions & Enablement (WASE) with an emphasis on Solutions Implementation, Acquisition, Transformation and Journey projects. As an AEL, you provide technical leadership across analytics work that may have enterprise mandate and partner directly with senior stakeholders to explain complex analysis and drive decision-ready outcomes.
Requirements
- Bachelor's or Master's degree in Statistics, Mathematics, Economics, Computer Science, Data Science, Finance, or a related quantitative discipline.
- 5 years of experience in analytics, consulting, or data science.
- Experience working directly with business stakeholders and senior leadership.
- Advanced proficiency in SQL and Python programming skills.
- Hands-on experience with Azure Databricks and PySpark for large-scale analytics.
- Strong foundation in statistical inference, hypothesis testing, regression, sampling methodologies, and experimental design.
- Experience building scalable, reusable analytical assets and workflows.
- Familiarity with data visualization and presentation tools.
- Excellent executive presentation and storytelling skills.
- Strong consulting and stakeholder management capabilities.
- Ability to simplify complex analytical concepts for non-technical audiences.
- Strong problem-solving skills with a bias toward delivering measurable business outcomes.
- Experience mentoring or reviewing the work of junior analysts.
Responsibilities
- Lead the end-to-end delivery of initiatives, from problem framing to analysis, recommendations, and business adoption.
- Partner with business stakeholders to identify opportunities where data analytics can drive measurable business value.
- Collaborate with partners across analytics, data engineering, and technology to develop scalable and sustainable analytics solutions.
- Translate data-driven insights into actionable business recommendations.
- Able to perform hands-on data extraction, transformation, analysis, and modeling using SQL, Python, and PySpark.
- Build scalable analytical workflows and reusable assets to improve efficiency.
- Ensure data quality, analytical rigor, and reproducibility throughout the analysis lifecycle.
- Apply statistical techniques to evaluate causal impact, quantify uncertainty, and validate business outcomes.
- Provide technical leadership and analytical guidance to junior analysts.
- Conduct peer reviews of code and analytical solutions to ensure accuracy, efficiency, and adherence to development standards.
- Coach team members on best practices, coding standards, and analytical storytelling.
- Act as a strategic thought leader to business stakeholders, build strong partnerships with business leaders and cross-functional teams, confidently challenge assumptions, shape problem definitions, and influence decisions to balance business needs with analytical rigor and feasibility.
- Translate complex analytical concepts into clear, business-friendly recommendations.
- Present outcomes, insights and recommendations to senior executives with confidence and clarity.
- Influence business decisions through evidence-based storytelling and data-driven recommendations.
Benefits
- health and well-being benefits
- savings and retirement programs
- paid time off
- banking benefits and discounts
- career development
- reward and recognition programs
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
