Senior Manager, Advanced Analytics/Data Science

Work Location:

Mount Laurel, New Jersey, United States of America

Hours:

40

Pay Details:

$122,304 - $199,680 USD

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 at TD. Our 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.

Line of Business:

Analytics, Insights, & Artificial Intelligence

Job Description:

Department and Role Overview:

The US Financial Crime Risk Modeling & Advanced Analytics team within US Financial Crime department is responsible for developing, maintaining, and enhancing the Enterprise Anti-Money Laundering / Counter-Terrorism Financing (AML/CTF) models/AI solutions to comply with regulatory requirements/changes and internal policies, support TD's global AML/CTF strategies, address emerging risks, and be in accordance with best industry practice.

We are seeking a highly skilled Data Scientist to join our team. In this pivotal role, you will be responsible for, but not limited to, researching and executing innovate AI solutions to help the firm identify and manage Money Laundering / Terrorism Financing risks more effectively and meet regulatory requirements. This incumbent is expected to be an individual contributor with extensive hands-on Python coding and machine learning modeling experience. Team support will be available when needed.

The above details are specific to the role which is outlined in the general description below.

The Lead Data Scientist is responsible for collecting data and using a wide range of data science techniques, including but not limited to data wrangling, profiling and visualization, statistical inference, to uncover actionable insights or build analytics solutions that guide decision making and strategic planning.

In addition, the Lead Data Scientist provides oversight and consultative advice and guidance to others as the lead or top Data Scientist with enterprise or significant cross business mandate. This role may also evaluate, investigate and identify technical solutions and provide leading-edge techniques and lead innovation to create methodologies to solve a wide array of complex business or enterprise issues.

Depth & Scope:

• Delivers advanced analytical capabilities above and beyond existing methods
• Exceptionally leads and runs analytical projects autonomously and creates and effectively delivers analytical presentations for executive audiences/stakeholders
• Showcases advanced level peer leadership, impacts and influences partner, and may mentor/coach peers
• Extensive understanding of the business supported and the overall bank with deep expertise and highly specialized knowledge of analytical concepts and techniques
• Acts as a key business partner, guides and collaborates with business leaders to prioritize and identify key business needs and provides impactful analytical insights

Education & Experience:

• 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;
• 7+ year of relevant experience; higher degree education and research tenure can be counted

Preferred Skills:

• Experience in Financial Crimes / Compliance Risk Analytics.
• Experience in optimization / tuning of Anti-Money Laundering (AML) and Counter-Terrorism Financing(CTF) solutions.
• Language including large language modeling experience is desired.

Customer Accountabilities:

• 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
• Uses a wide range of programing languages (e.g. Python) and techniques for extracting and preparing data, applying statistics and various advanced an