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TDVerified from TD's careers page · Workday

Data Scientist III (US) - FCRM

  • Mount Laurel, New Jersey, USA
  • On-site
  • $96,130 to $155,950
  • Posted Nov 6, 2026

Visa sponsorship: the posting says the employer will not sponsor a visa for this role.

At a glance

Data Scientist III (US) - FCRM at TD, an on-site role based in Mount Laurel, New Jersey, USA. Pay stated in the posting: $96,130 to $155,950. Posted on 6 November 2026, read from TD's own careers page (Workday), which RealAnalystJobs re-checks daily and removes the role when it closes. The posting says the employer will not sponsor a visa for this role.

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: ATTN: 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 : This position will be responsible for creating, developing, and maintaining a range of AML typologies, leveraging analytics to proactively identify and mitigate financial crime risks. The role involves close collaboration with cross-functional teams, supporting Financial Intelligence Units (FIU) through targeted data analysis, and contributing to strategic initiatives that strengthen our AML efforts across the organization. The individual will oversee the successful execution of multiple projects, ensuring they are completed within established timelines and providing a second level of oversight throughout. Prior experience and expertise with machine learning, Microsoft Azure, Python, SQL, and Databricks are essential for this position, and familiarity with both generative and agentic AI is highly valuable as we continue to advance our analytics capabilities. 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 : • Experience in Financial Crimes / Compliance Risk Analytics field • Experience in generating data and analytics insights and assisting financial institutions with addressing the efficiency and effectiveness of transaction monitoring systems • Experience with data transformation, ETL, and combining data from multiple sources to create analytics reports • Hands-on experience developing, validating, and deploying machine learning models • Experience with Microsoft Azure, Python, SQL, and Databricks • Experience with both generative and agentic AI 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 cros

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