Data Scientist III - FCRM Risk Modeling

Responsibilities

The Data Scientist III provides technical leadership in developing and maintaining enterprise-level anti-money laundering and counter-terrorism financing models. They collaborate with business owners to translate complex problems into viable data science solutions and visualize insights for stakeholders.

Requirements

Candidates should possess an undergraduate or advanced technical degree in a quantitative field and at least 5 years of relevant experience. Proficiency in Python and SQL is required, along with a strong foundation in machine learning and statistical modeling.

Skills

• Data science
• Python
• SQL
• Machine learning
• Regression
• Classification
• Anomaly detection
• Financial crimes
• Compliance risk analytics
• GenAI
• LLM
• Data modeling
• Statistical validation
• Data mining
• Risk management

Benefits

• Health and well-being benefits
• Savings and retirement programs
• Paid time off
• Vacation PTO
• Flex PTO
• Holiday PTO
• Banking benefits and discounts
• Career development
• Reward and recognition

About this role

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 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:
Eligibility Requirements
Applicants must be either a U.S. citizen or a U.S. Lawful Permanent Resident (Green Card Holder) must not require current or future TD sponsorship. Work Visa Sponsorship This role is not eligible for TD work visa support or sponsorship, including H-1B, F-1 OPT/STEM OPT, TN, or other work visa authorizations.

Job Description:
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.

Department 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 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

Depth & Scope:
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

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

Preferred Skills:
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

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 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

Shareholder Accountabilities:
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 enterprise frameworks or methodologies that relate to activities for business area
Ensures respective programs/policies/practices are well managed, meet business needs, comply with internal and external requirements, and align with business priorities
Participates in cross-functional/enterprise initiatives as a subject matter expert helping to identify risk/provide guidance for complex situations
Monitors service, productivity and assesses efficiency levels within own function and implements continuous process/performance improvements w...

About TD

Banking · 10,001+ employees · headquartered in Toronto, Ontario