Senior Manager, Data Science - FCRM Modeling

Work Location: New York, New York, United States of America Hours: 40 Pay Details: $123,050 - $201,170 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: ATTENTION: This role is not eligible for TD work visa support or sponsorship (e.g., H-1B, F-1 OPT/STEM OPT, TN or other work visa authorizations). Applicants must be either a US Citizen or have a US Resident Green Card authorization, without current or future need for TD sponsorship . Job Description: The Senior Manager, Data Science leads a specialized team of data professionals varying in size and complexity that are responsible for aiding to drive changes and improvement in business practices through data science. This role manages the overall data scientist team or function for a key business which may include Modelers and/or Data Scientist roles. This role may also oversee the development of data models, data mining and analytic solutions. 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, and address emerging risks, in accordance with best industry practice. We are seeking a Data Science Senior Manager to join us to innovate, drive, and support innovation initiatives and business as usual operations in across the FCRM areas including, but not limited to, customer rating, sanctions screening, transaction monitoring, emerging risk, model performance monitoring, analytics, and reporting. This role will lead development of tools to improve risk detection of complex areas and enhance process efficiency in business operations across FCRM, leveraging the latest tools such as LLMs. They will also own interaction with key stakeholders and any applicable model lifecycle activities. Depth & Scope: Provides people management leadership by hiring the best talent, setting goals, developing staff, managing employee performance and compensation decisions, promoting teamwork and handling any/all disciplinary actions, as required Oversees and leads a large and/or highly complex and diverse analytical function for an area of significant risk, complexity or scope Strategic partner to leadership team on the management of the portfolio and financials, with deep industry, external/internal, enterprise knowledge, recognizing and anticipating emerging trends and identifying operational efficiencies and opportunities with other business management/enterprise areas Facilitates key strategic discussions and provides thought leadership to executive audience (output may include strategic roadmap and/or deliverables/frameworks/short to long term goals etc.) Sets operational team direction and collaborates with others to execute on common goals Focuses on longer range planning for functional area (e.g. 12 months or greater) 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: Minimum of 7 years of relevant experience required; candidates with 5 years of highly relevant experience may also be considered. Demonstrated experience leading data science, analytics, or innovation initiatives for enterprise-scale solutions in production environments. Proficiency in Python, SQL, or equivalent programming languages. Experience in financial crimes, compliance risk analytics, model risk, or related risk management domains. Strong understanding of large language models (LLMs), machine learning, and quantitative risk analysis. Experience optimizing, testing, and tuning AML/CTF solutions. Experience developing dashboards, web applications, or other user-facing analytical tools. Proven experience managing teams and collaborating effectively across cross-functional stakeholders. Customer Accountabilities: Leads team of Data Scientists and provides day-to-day direction as needed Acts as People Manager and is responsible for ongoing coaching and development, setting objectives, assessing performance Works closely with business owners to identify opportunities and serves as an ambassador for data science Leads and oversees the design and delivery of enterprise analytic solutions for customers Works in a highly interactive, team-oriented environment with Big Data developers, and analytical experts Collaborates with business partners to shape and prioritize ad hoc analysis Shareholder Accountabilities: Provides analytical thought leadership and stays current on developments in data mining and the application of data science Manages workload of data science team; assigning data request to staff based on skills and development needs Supports execution with excellence on key initiatives/programs Designs effective test and learns for various programs or scenarios Develops business specific plans; ensures work and resources are aligned to support objectives Identifies opportunities for business growth within a specific business or function by identifying potential use cases and value drivers Proactively supports the identification of issues, trends and opportunities, and brings forward recommendations based on judgment and facts Leads team to prepare framework to succinctly take complex data and translate it into clear and concise recommendations Ensures deep understanding and contributes to the achievement of the business strategy, goals, and objectives Ensures team adheres to enterprise frameworks and methodologies related to overall business management activities Leads relationships with corporate and/or control functions to ensure alignment with enterprise and/or regulatory requirements Supports team in staying knowledgeable on emerging issues, trends and evolving regulatory requirements and assesses potential impacts to the Bank Assesses/identifies key issues and escalates to appropriate levels and relevant stakeholders and business management where required Identifies, mitigates and reports on risk issues per enterprise policy/guidance and ensures appropriate escalation processes are followed Ensures business operations are in compliance with applicable internal and external requirements (e.g. financial controls, segregation of duties, transaction approvals and physical control of assets) Leads relationships with business lines / corporate and/or control functions to ensure alignment with enterprise and/or regulatory requirements Leads or contributes to cross-functional/enterprise initiatives as an organizational or subject matter expert helping to identify risk/provide guidance for complex situations Protects the interests of the organization – identifies and manages risks, and escalates non-standard, high-risk transactions/activities as necessary Manages oversight process, risk-based identification and monitoring of related risks and regulatory compliance across the supported functions, while e