POSITION OVERVIEW:

As a key member of Financial Crimes Analytics & Insights Team, this position will play a pivotal role in enabling the 1st line to combat financial crimes risks through various ad hoc analyses and priority initiatives.

Key Responsibilities include:

• Leverage various statistical and advanced techniques to identify emerging risks, patterns and typologies to predict financial crime activities and risks.
• Conduct ad hoc analyses to address business and regulatory body questions or inquiries, provide actionable insights.
• Develop and maintain scalable data model to support the analytics framework.
• Translate data into consumable insights, and present findings to businesses, gather of feedback, and integrate feedback to improve predictions.
• Work with partners from AMCB AI2 and AMCB DaaS to explore new data sets and how they can be leverage for financial crimes.
• Based on the above, develop interactive, self-service solutions to arm business users the information needed to conduct review and spot outliers.

Preferred Qualifications :

• Technical Skills: ETL, Python, PySpark, R, SQL, Databricks, Azure, Tableau/PowerBI
• Proven experience in data modeling, a dvanced analytics, and statistical analysis using programming languages such as Python
• Strong communication and relationship management skills to effectively collaborate with cross-functional teams and support stakeholders
• Strong analytical skills with experience in detecting patterns and anomalies in large datasets
• Ability to interpret complex data and translate it into actionable insights and present them to both technical and non-technical stakeholders
• Experience with building data model such as data vault, slow moving dimension, or star schema.
• Experience in building LLMs agent for data analytics projects
• Experience with machine learning and statistical modeling is a plus
• Demonstrated ability in building and maintaining large-scale data pipelines and architectures.
• Experience with Azure cloud a plus
• Knowledgeable of data management & governance and its importance on data consumption

can be counted.

WHO WE ARE:

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 deliver legendary customer experiences to 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 the Bank, those we serve, and the economies we support. We are guided by our vision to Be the Better Bank and our purpose to enrich the lives of our customers, communities and colleagues.
TD is deeply committed to being a leader in customer experience, that is why we believe that all colleagues, no matter where they work, are customer facing. As we build our business and deliver on our strategy, we are innovating to enhance the customer experience and build capabilities to shape the future of banking. Whether you’ve got years of banking experience or are just starting your career in financial services, we can help you realize your potential. Through regular leadership and development conversations to mentorship and training programs, we’re here to support you towards your goals. As an organization, we keep growing – and so will you.

• Leverage various statistical and advanced techniques to identify emerging risks, patterns and typologies to predict financial crime activities and risks.
• Conduct ad hoc analyses to address business and regulatory body questions or inquiries, provide actionable insights.
• Develop and maintain scalable data model to support the analytics framework.
• Translate data into consumable insights, and present findings to businesses, gather of feedback, and integrate feedback to improve predictions.
• Work with partners from AMCB AI2 and AMCB DaaS to explore new data sets and how they can be leverage for financial crimes.
• Based on the above, develop interactive, self-service solutions to arm business users the information needed to conduct review and spot outliers