Data Scientist II

Line Of Business

Analytics, Insights, & Artificial Intelligence

Markham, Ontario, Canada

37.5

$81,600 - $115,200 CAD

TD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience  compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The base pay actually offered may vary based upon the candidate's skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs.

As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.

Are you passionate about analytics and working with big data? Want to drive change and become a subject matter expert in fraud management? If so, join the Canadian Fraud Performance Management Team.

You would be responsible for mining big data to discover actionable fraud insights, and to develop and implement fraud strategies in a fast paced environment. You would manage evolving fraud threats while taking into consideration TD risk appetite, Customer and operational experience. With strong technical, analytics background you would join the team to learn and manage 1st and 3rd party fraud.

• Develop and deploy product and channel-specific fraud strategies to reduce fraud risk balancing loss, Customer experience and operational capacity
• Identify new fraud vectors and optimize existing rules using SQL, Python, and fraud authentication solutions
• Conduct intra-day and weekly monitoring across products, channels, and risk segments
• Provide ad-hoc analysis to support decision-making at the executive level
• Continually optimize, improve, and strengthen fraud strategy and analytics capabilities
• Independently investigate new, high-risk fraud threats under tight timelines

• Advanced proficiency in SQL, Python for data analysis, automation, and reporting
• 2+ years of hands-on experience in an analytical capacity
• Motivated to constantly strive to find innovative data-informed ways to enhance capabilities
• In-depth knowledge of data science tools such as Num Py, pandas, matplotlib or R equivalent
• Ability to communicate strategy analysis to both technical and non-technical team members
• Passion and drive to take initiative and work independently under tight timelines
• Ability to effectively manage multiple work streams and tasks at the same time
• Undergraduate degree from a technical domain (e.g. computer science, engineering, mathematics, or statistics)

• Experience in fraud management is an asset
• Machine learning development and deployment is an asset
• Automation experience is an asset

TD is one of the world's leading global financial institutions and is the fifth largest bank in North America by branches/stores. Every day, we strive to make every interaction, product, and experience remarkably human and refreshingly simple for over 27 million households and businesses in Canada, the United States and around the world. More than 95,000 TD colleagues bring their skills, talent, and creativity to foster deeper relationships, ensure disciplined execution, and build a simpler, faster banking experience.

TD is deeply committed to being a leader in client experience, that is why we believe that all colleagues, no matter where they work, are client facing. Together, we are reimagining what banking can be for our clients, colleagues and communities.

Our Total Rewards package reflects the investments we make in our colleagues to help them and their families achieve their financial, physical, and mental well‑being goals. Total Rewards at TD includes a base salary, variable compensation, and several other key plans such as health and well‑being benefits, savings and retirement programs, paid time off, banking benefits and discounts, career development, and reward and recognition programs.

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