TD is seeking a highly skilled Senior Data Scientist to join their Financial Crime Risk Modeling & Advanced Analytics team. The primary business problem is to develop and monitor financial crime risk models, leveraging data science expertise to identify opportunities, extract insights from big data, and translate complex data analysis into actionable solutions for decision-makers and stakeholders.
Requirements
- Hands-on experience in modeling with strong coding skills in Python and SQL.
- Experience with LLM and knowledge of the AML domain is a plus, along with experience in SAS coding and Transaction Monitoring.
- Uses a wide range of programing languages (e.g. Python) and techniques for extracting and preparing data, applying statistics and various advanced analytics, along with business acumen to extract insights from the big data.
- Visualizes insights from the data to tell and illustrate stories that clearly convey the meaning of results to decision-makers and stakeholders at every level of technical understanding.
- Collaborates with other partners, such as data and business analysts, software engineers, data engineers, and application developers to develop scalable and sustainable data science solutions that retains long term benefit to the business.
- Analytical thought leadership and stays current on developments in data mining and the application of data science.
- Educates the organization on approaches, such as testing hypotheses and statistical validation of result.
Responsibilities
- Provides technical leadership across the overall Analytics function which may have an enterprise mandate.
- Generally provides deep technical knowledge and expertise in client interactions to explain complex data analysis related material.
- Responsible for financial crime risk model development and monitoring.
- Works independently on activities related to analysis, design and support of technical data management solutions on various projects ranging in complexity and size.
- Uses a wide range of programing languages (e.g. Python) and techniques for extracting and preparing data, applying statistics and various advanced analytics, along with business acumen to extract insights from the big data.
- Visualizes insights from the data to tell and illustrate stories that clearly convey the meaning of results to decision-makers and stakeholders at every level of technical understanding.
- Collaborates with other partners, such as data and business analysts, software engineers, data engineers, and application developers to develop scalable and sustainable data science solutions that retains long term benefit to the business.
Other
- Undergraduate degree or advanced technical degree preferred (e.g., math, physics, engineering, finance or computer science) Graduate's degree preferred with either progressive project work experience or
- 5+ year of relevant experience; higher degree education and research tenure can be counted
- Graduate degree candidates with ~4 years' experience will be considered for this role.
- Works closely with business owners to identify opportunities and serves as an ambassador for data science.
- Is familiar with the business context and data infrastructure and can translate business problems to viable data science solutions.
