Principal Data Scientist (US)

Work Location:

Southfield, Michigan, United States of America

Hours:

40

Pay Details:

$148,720 - $223,080 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 Principal Data Scientist is responsible for collecting data and using a wide range of data science techniques, including but not limited to data wrangling, profiling and visualization, statistical inference, to uncover actionable insights or build analytics solutions that guide decision making and strategic planning.

In addition, the Principal Data Scientist provides technical expertise with a focus on bank and industry-wide solutions that addresses capability gaps to create opportunities for significant value for customers.

Own end-to-end decisioning and pricing optimization engine, use large-scale historical and market data to form hypotheses, conduct analyses, develop machine learning models, evaluate and implement model and drive business decisions 

Analyze large-scale data and apply statistical models to recommend insights and solve business objectives

Collaborate with business partners to identify and refine business strategies, analyze alternative deal structures and deliver business P&L expectations

Stay up to date on industry trends and optimization methodologies in auto finance markets

Depth & Scope:

• Delivers advanced analytical capabilities above and beyond existing methods
• Exceptionally leads and runs analytical projects autonomously and creates and effectively delivers analytical presentations for executive audiences/stakeholders
• Showcases advance level peer leadership, impacts and influences partner, and may mentor/coach peers
• Extensive understanding of the business supported and the overall bank with deep expertise and highly specialized knowledge of analytical concepts and techniques
• Acts as a key business partner, guides and collaborates with business leaders to prioritize and identify key business needs and provides impactful analytical insights
• Leads authority on Data Science concepts, principals, practices and standards
• Thought leader on IT risk-based approaches to Data Science
• Sets the direction and oversees the work of other Data Science professionals on complex, highly visible projects of significant profile, strategic importance, and enterprise impact to the bank
• Provides consultative and strategic guidance to executive leadership
• Principal Data Science assigned to work autonomously on high profile, complex and high-risk technology initiatives with significant impact to the organization
• Primarily works at the enterprise level

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;
• 10+ year of relevant experience; higher degree education and research tenure can be counted

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
• Provides deep technical leadership and expertise to support and defi