Principal Data Scientist

TD Bank is seeking a Principal Data Scientist to drive analytics that support decision-making and long-range planning. This role focuses on end-to-end ownership of a decisioning and pricing optimization engine, applying advanced data science methods to convert large-scale historical and market inputs into actionable outcomes. You will also provide technical leadership across complex, enterprise-level initiatives and guide executive communication of results.

• Collect and work with data using a broad set of data science techniques, including data wrangling, profiling and visualization, and statistical inference, to uncover actionable insights or build analytics solutions that inform strategic decisions.
• Provide technical expertise focused on bank and industry-wide solutions, addressing capability gaps to create meaningful value for customers.
• Own the end-to-end decisioning and pricing optimization engine, using large-scale historical and market data to form hypotheses, run analyses, develop machine learning models, evaluate model performance, implement models, and drive business decisions.
• Analyze large-scale datasets with statistical models to recommend insights and solve business objectives.
• Collaborate with business partners to identify and refine strategies, analyze alternative deal structures, and deliver business P&L expectations.
• Stay current on industry trends and optimization methodologies in auto finance markets, delivering advanced analytical capabilities beyond existing methods.
• Lead analytical projects autonomously and create analytical presentations for executive audiences and stakeholders.
• Demonstrate advanced peer leadership by influencing partners and mentoring or coaching peers where needed.
• Serve as a key business partner by guiding business leaders to prioritize business needs and translate business problems into viable data science solutions.
• Act as the authority on data science concepts, principles, practices, and standards, including thought leadership on IT risk-based approaches to data science.
• Set direction and oversee work of other data science professionals on complex, highly visible, strategic, and enterprise-impacting projects.
• Provide consultative and strategic guidance to executive leadership, primarily working at the enterprise level.
• Work with stakeholders to identify new analytical trends and data needs, generate hypotheses, and build analytical models to answer high-impact business questions.
• Protect organizational interests by identifying and managing risks, escalating non-standard high-risk activities when necessary.
• Account for creating and implementing processes and systems to extract knowledge or insights from structured and unstructured data.
• Collaborate with data and business analysts, software engineers, data engineers, and application developers to build scalable, sustainable solutions with long-term value.
• Lead or facilitate action and remediation plans to address performance, risk, and governance issues; maintain alignment with enterprise and regulatory requirements.
• Keep current on emerging issues, trends, and evolving regulatory requirements, assessing potential impacts and supporting a culture of risk management and control aligned with risk appetite.
• Participate in enterprise initiatives as a subject matter expert, helping identify risk and providing guidance for complex situations.
• Contribute to team growth through mentorship, knowledge transfer, and sharing best practices, while building productive relationships with internal and external stakeholders.
• Support a fair, positive, and equitable environment, and act as a brand ambassador for the business area or function and for the bank.

• Undergraduate degree or advanced technical degree preferred (e.g., math, physics, engineering, finance, or computer science).
• Graduate’s degree preferred, with progressive project work experience, or 10+ years of relevant experience (higher degree education and research tenure can be counted).
• 10 years minimum experience.

• Python
• Machine learning models

• Location:
  
  Southfield, Michigan, United States (onsite)
• Hours:
  
  40
• Pay: $148,720 - $223,080 USD per year

• Base salary and variable compensation/incentive awards, including eligibility for cash and/or equity incentive awards through participation in an incentive plan.
• Health and well-being benefits
• Savings and retirement programs
• Paid time off including Vacation PTO, Flex PTO, and Holiday PTO
• Banking benefits and discounts
• Career development, reward and recognition, and training and onboarding sessions
• Regular career, development, and performance conversations with your manager
• Access to an online learning platform and mentoring programs

• Line of business:
  Analytics, Insights, & Artificial Intelligence
• Domestic travel:
  Occasional;
  International travel:
  Never