Data Scientist III

TD•Toronto, ON

1d•CA$96,900 - CA$136,800•Onsite

About The Position

Within Analytics, Insights & Artificial Intelligence (AI2), the Customer Assistance (CA) team leverages data, analytics, and AI to improve customer outcomes, optimize operational performance, strengthen risk management, and drive measurable business value. Partnering closely with business, Risk, Technology, and Operations leaders, the team delivers advanced analytics, machine learning, business intelligence, and AI solutions across customer journey analytics, collections optimization, forecasting, performance measurement, automation, model monitoring, and emerging AI capabilities. As part of a collaborative team of data scientists, data engineers, and business partners, you will help solve complex business challenges and enable data-driven decision-making that improves both customer and business outcomes. As a Data Scientist III, you will be a technical leader responsible for designing, delivering, and sustaining advanced analytics, AI, and business intelligence solutions that support the strategic priorities of the Customer Assistance business. You will partner with many stakeholders to translate complex business challenges into scalable analytical solutions. Using advanced analytics, machine learning, experimentation, and AI techniques, you will identify opportunities to improve customer outcomes, optimize operations, strengthen risk management, and drive measurable business value. This role requires strong technical expertise, business acumen, stakeholder management, and a passion for innovation to help advance CA's analytics and AI capabilities.

Requirements

5+ years of experience in data science, advanced analytics, or a related quantitative field.
Degree in Data Science, Statistics, Computer Science, Engineering, Mathematics, Finance, or related discipline.
Advanced proficiency in Python, SQL, and modern analytics platforms (e.g., Databricks).
Experience applying statistical modeling, machine learning, predictive analytics, and experimentation techniques to business problems.
Strong foundation in statistics and working with large structured and unstructured datasets.
Experience delivering production-ready analytics solutions in cloud environments.
Strong communication and data storytelling skills, with the ability to influence business and technical stakeholders.
Knowledge of data governance, risk management, privacy, compliance, and responsible AI practices.
Experience with Power BI, Tableau, or similar visualization tools.

Nice To Haves

Experience in banking, financial services, collections, customer assistance, risk, or operations analytics is an asset.

Responsibilities

Lead advanced analytics, machine learning, and AI initiatives that deliver measurable business value.
Translate business challenges into scalable analytical solutions and actionable insights.
Develop predictive models, reporting frameworks, dashboards, and monitoring capabilities.
Leverage Python, PySpark, SQL, and cloud technologies to analyze large and complex datasets.
Quantify business impact, define KPIs, and measure value realization using robust analytical methodologies.
Identify opportunities to improve customer outcomes, operational effectiveness, portfolio performance, and risk management.
Present complex findings through executive-ready insights, visualizations, and recommendations.
Partner closely with business, technology, and risk stakeholders to deliver strategic outcomes.
Champion data governance, data quality, and responsible AI practices.
Drive innovation through experimentation, automation, and adoption of emerging AI capabilities.
Effectively manage multiple priorities while maintaining high-quality deliverables and stakeholder satisfaction.