Data Scientist II - Remediation

TD•Toronto, ON

1d•Onsite

About The Position

Within Canadian Personal Banking Analytics, Insights, and AI (CPB AI2), the Real Estate Secured Lending (RESL) Remediation & Regulatory team supports day-to-day operations of RESL Issue Management and Customer Remediation through data-driven insights. We help quantify issue materiality, identify impacted customer segments, and ensure efficient, effective remediation. We are also responsible for delivering timely updates to regulators, helping safeguard TD’s brand and uphold our strong reputation. We are seeking a Data Analyst / Data Scientist to partner closely with business teams to investigate, analyze, and solve issues affecting our RESL customers, while responding to regulatory data requests with precision and integrity. If you're detail-oriented, passionate about problem-solving, and thrive on uncovering meaningful insights from data, this role is for you.

Requirements

Undergraduate or advanced degree in a technical field (e.g., Math, Statistics, Engineering, Computer Science, or Finance).
3+ years of experience in data analytics, data science, or a similar role; graduate-level research or thesis work may count toward experience.
Proficient in Python and SQL; working knowledge of PySpark and Azure Databricks or equivalent cloud-based platforms is an asset.
Proficiency in Tableau, Power BI, and Excel for interactive reporting.
Experience working with large datasets and customer-sensitive and transactional data.
Strong analytical and problem-solving skills.
Excellent communication and stakeholder management.
Ability to manage multiple priorities in a fast-paced, highly-regulated environment.
Attention to detail, integrity, and a customer-first mindset.

Nice To Haves

Working knowledge of PySpark and Azure Databricks or equivalent cloud-based platforms.
Experience in RESL products (Mortgage, Home Equity Line of Credit, … etc.)

Responsibilities

Build a deep understanding of the RESL business context, data infrastructure, and analytical needs.
Translate complex business problems into viable and scalable data solutions.
Use programming languages such as Python, PySpark, and SQL to extract, transform, and analyze large datasets.
Leverage business acumen to uncover insights that drive action.
Proactively engage with data owners to identify and acquire the necessary data sources required to support business analysis, regulatory responses, and remediation efforts.
Partner with business stakeholders to define issues, investigate root causes, and quantify customer and operational impacts.
Translate business needs into analytical requirements and deliver actionable, data-driven solutions.
Support business validation efforts by providing accurate data for testing and verification of implemented solutions, ensuring remediation effectiveness and integrity.
Gather and prepare impacted customer data for communication and remediation.
Assist in calculating financial harm, preparing customer notification packages, and developing remediation strategies with business partners.
Design and automate recurring regulatory and business reports to improve efficiency, consistency, and accuracy of deliverables.
Communicate complex insights clearly through effective visualizations and storytelling tailored to both technical and non-technical audiences.
Work independently and collaboratively with data engineers, product managers, and business stakeholders to ensure alignment and progress across initiatives.
Actively contribute ideas for process and solution improvements, focusing on increasing the effectiveness, efficiency, and impact of analytics within the team.
Follow enterprise data governance and privacy standards rigorously, especially when working with sensitive customer information.
Ensure responsible handling, storage, and sharing of data at all times.
Be an active, engaged, and supportive team member in a collaborative and high-performance environment.
Promote a positive, inclusive work culture centered around service, innovation, and continuous improvement.
Participate in training, performance feedback, and knowledge-sharing initiatives.
Keep stakeholders informed about key project updates and potential risks or blockers.