Data Scientist III - Financial Crimes Modeling

This a Full Remote job, the offer is available from: Massachusetts (USA), New Jersey (USA), New York (USA) Work Location: New York, New York, 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: 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 a Data Science specialist 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:
• In lieu of 5+ years of relevant experience, we will consider 3+ years of relevant experience
• Proficient with Python or equivalent programming language and SQL
• Experience in Financial Crimes / Compliance Risk Analytics is a plus
• Experience in optimization / testing / tuning of AML/CTF solutions, particularly transaction monitoring systems
• Experience in machine learning model development, validation, and deployment; experience with LLM-based solutions a plus
• Familiarity with cloud platforms (Azure) and modern data stack tools a plus 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 organiz

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