Data Scientist III (Financial Crimes/Fraud Detection/AML) - Python/SQL/Tableau/ETL/Azure

Work Location:

Vienna, Virginia, United States of America

Hours:

40

Pay Details:

$95,264 - $155,376 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.

Position Overview:

As a key member of Pan-AMCB Analytics & Insights for financial crimes, the Data Scientist III will play a pivotal role in the design, development, and maintenance of a new Management Intelligence & Analytics Framework. This initiative aims to create an integrated and interactive platform for comprehensive monitoring of activities and risks across GAML stages, significantly enhancing risk mitigation capabilities.

Key Responsibilities include:

• Design and implement statistical models to analyze and predict financial crime activities and risks.
• Develop and maintain scalable data pipelines to support the analytics framework.
• Conduct ad hoc analyses to address business and regulatory body questions or inquiries, provide actionable insights
• Collaborate with a task force to create a holistic view of GAML intelligence, integrating feedback from both first and second-line leaders.
• Construct highly interactive, self-service tools for detailed data analysis and visualization.
• Continuously assess and refine the effectiveness of the analytics framework, leveraging advanced analytics to identify and mitigate emerging risks.

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 Qualifications:

• Proven experience in data modeling and engineering, with a strong background in using statistical programming languages such as Python.
• Demonstrated ability in building and maintaining large-scale data pipelines and architectures.
• Excellent problem-solving abilities and a track record of working effectively in dynamic, cross-functional teams.
• Effective communication skills, capable of conveying complex concepts to a broad range of stakeholders.
• knowledge of GAML processes, regulations, and risk management practices is an asset
• Technical Skills: ETL, Python, PySpark, R, SQL, Databricks, Alteryx, Tableau

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