Data Scientist III - FCRM Risk Modeling

Data Scientist III

Work Location:

Mount Laurel, New Jersey, United States of America

Hours:

40

Pay Details: $96,130 - $155,950 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  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.

The Data Scientist III provides technical leadership across the overall Analytics function which may have an enterprise mandate. This role generally provides deep technical knowledge and expertise in client interactions to explain complex data analysis related material.

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 talented data scientists to join us to innovate, drive, and support initiatives and business as usual operations in multiple functional areas including, but not limited to, customer rating, sanctions screening, transaction monitoring, emerging risk, model performance monitoring, analytics, and reporting.

• Generally accountable for a significant business management area that typically has enterprise-wide impact or accountability
• Enterprise or functional expert, requiring broad managerial and deep specialized knowledge at the enterprise, business, regulatory and industry levels
• Undertakes and completes a variety of complex initiatives requiring seasoned specialist knowledge and/or the integration of cross functional processes
• Position typically deals with senior/executive management
• Works independently on activities related to analysis, design and support of technical data management solutions on various projects ranging in complexity and size
• Focuses on longer-range planning for functional area (e.g. 12 months or greater)
• May manage and prioritize multiple projects at a given time

• 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

• Strong foundation in regression, classification, and machine learning models and anomaly detection techniques
• Proficiency with Python and SQL is a must
• Experience in Financial Crimes / Compliance Risk Analytics is a plus
• Hands-on experience with GenAI applications is a strong plus, including but not limited to fine-tuning or prompting LLMs
• Ability to build analytical solutions using LLM APIs, and use GenAI applications to develop data labeling solutions

• 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 programming 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
• Solicits and offers ideas for improving business processes through insights with the objective of improving effectiveness and efficiency
• Educates the organization on approaches, such as testing hypotheses and statistical validation of result
• Helps the organization understand the principles and the math behind the scientist process to drive organizational alignment
• Translates up to date information into continuous improvement activities that enhances performance
• Adheres to…