Work Location:
New York, New York, United States of America
Hours:
40
Pay Details:
$96130.00 - $155950.00 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:
Please be aware that this role within this line of business is only eligible to those candidates that are U.S. Citizens / Green Card Holders, and will not be 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 have authorization to work in the United States without current or future need for TD sponsorship.
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.
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 relevantexperience; higher degree education and research tenure can be counted
Preferred Skills:
- Someone with 3-7 years experience in model risk management as Model Governance, Model Validate, or Model Developer. Alternatively, someone managed model risk programs for the these model risk quant teams or AI/ML data scientists with deep domain knowledge of Model Risk or AI/ML risk management.
- Experience/knowledge of Financial Crime Risk Management practices and associated regulations.
- Excellent project management experience, including planning, execution, and on-time delivery.
- Good analytical and critical thinking, proactive attitude, and collaborative approach to engage internal and external partners to deliver business results.
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 me