Data Scientist III

TD•Toronto, ON

2d•Onsite

About The Position

The Canadian Personal Banking (CPB) Analytics, Insights and Artificial Intelligence (AI2) team supports the day-to-day activities of the CPB businesses, working with business partners to address their analytics needs by providing end-to-end support of data, reporting, analytics, insights, and artificial intelligence solutions. The Real Estate Secured Lending (RESL) AI2 team is responsible for supporting product and pricing strategies, product development, customer lifecycle management, and the financial performance of Mortgage and Home Equity Line of Credit Products. This Data Scientist III, Real Estate Secured Lending role reports into the Senior Manager, Data Science. As a Data Scientist in Real Estate Secured Lending, you will be responsible for leading the development, maintenance, and enhancement of pricing models to support decision making. You will collaborate closely with business owners and partners to understand business objectives, identify data needs, and deliver actionable insights that drive strategic improvement. The team routinely collaborates with diverse stakeholders across the RESL business, Treasury, Analytics, Insights and Artificial Intelligence, and more.

Requirements

Undergraduate or advanced technical degree (e.g., math, statistics, engineering, finance, or computer science); graduate's degree preferred with progressive work experience
5+ years of relevant experience in analytics, data science and/or consulting, ideally in an influencing or advisory capacity.
Effective stakeholder and project management skills with demonstrated experience leading large scale analytics projects individually contributing and guiding other data scientists from idea to production deployment.
Demonstrated knowledge and application of analytical languages/tools/platforms such as Python / Pyspark, SQL, Tableau, PowerBI, Databricks, on large datasets with a track record of delivering business impact and results.
Strong problem-solving skills, with the ability to navigate ambiguous issues and deliver well-defined solutions.
Excellent communication skills, with experience presenting insights to executive leaders and business partners.
Able to participate as part of a team with targeted deliverables, working on initiatives designed to improve decisions, processes, systems, and applications which support our businesses.

Nice To Haves

Knowledge and demonstrated experience developing and implementing data driven pricing strategies are considered a strong asset.
Knowledge of consumer lending, Real Estate Secured Lending, pricing and hedging strategies/modeling considered a strong asset.

Responsibilities

Lead development, validation, and maintenance of pricing models using statistical, machine learning, and data mining techniques.
Act as lead and individual contributor to analytics projects developing and executing against project plans including guiding other data scientists.
Partner with business stakeholders to understand objectives, gather requirements, and translate business needs into analytical solutions.
Use programming languages (Python, Pyspark, SQL) to extract and prepare data, apply statistics and various advanced analytics along with business acumen to inform recommendations and insights from large datasets.
Visualize insights from data to illustrate stories that clearly convey the meaning of results to decision-makers and stakeholders at every level of technical understanding.
Collaborate with other partners, such as AIML scientists, data and business analysts, software engineer, data engineers, and application developers to develop scalable and sustainable machine learning/data science solutions that retain long term benefit to the business.
Clearly communicate the value, principles and math behind the scientific process such as hypothesis testing and statistical validation to drive organizational excellence.
Provide thought leadership and/or industry knowledge for own area of expertise and participate in knowledge transfer within the team and business unit.