Data Scientist II at TD Bank
Toronto, ON, Canada -
Full Time


Start Date

Immediate

Expiry Date

30 Oct, 25

Salary

76800.0

Posted On

30 Jul, 25

Experience

3 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Tableau, Business Strategy, Data Visualization, Pandas, Power Bi, Transformation, Integration, Unsupervised Learning, Aws, Stored Procedures, Reinforcement Learning, Training, Model Development, Dashboards, Numpy, Finance, Machine Learning, Critical Thinking

Industry

Information Technology/IT

Description

JOB DESCRIPTION:

We are seeking a Data Scientist to support the CBP RESL Specialized Sales Force (SSF) business. SSF AI2 team supports the RESL Sales Channels (Mobile Mortgage Specialist, Broker, Builder and more). The team is responsible to provide end-to-end support of data, reporting, analytics, insights and artificial intelligence solutions to the business.

THE IDEAL CANDIDATE WILL HAVE EXPERIENCE:

  • Working with various and large datasets; experience with Personal Banking / RESL / Credits data & products is strongly preferred
  • Using multiple analytics techniques to support the business strategy.
  • Creating strong partnership with business partners.
  • Demonstrating critical thinking and structured problem-solving skills

REQUIRED QUALIFICATIONS & SKILLS

  • 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.
  • 3+ years of relevant experience; higher degree education and research tenure can be counted.

TECHNICAL SKILLS:

  • Programming Expertise: Proficiency in Python (including Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, and PySpark) and SQL (writing complex queries, stored procedures, and data extraction).
  • Machine Learning & AI: Hands-on experience with machine learning techniques, including supervised and unsupervised learning, reinforcement learning, and causal inference. Familiarity with generative AI (GenAI), large language models (LLMs), and statistical inferencing.
  • Model Development & Deployment: Experience building, training, and deploying machine learning models, including model pipelines, feature engineering, hyperparameter tuning, and model explainability.
  • Data Visualization: Proficiency in tools like Power BI, Tableau, or similar platforms to create impactful visualizations and dashboards.
  • Cloud Platforms: Experience with cloud-based data and AI/ML platforms (e.g., Azure, AWS, or GCP), including deploying and managing models in production environments.
  • Data Handling: Expertise in working with large, complex datasets, including data cleansing, transformation, and integration.
  • Analytical/Data Consultant: Strong understanding of data structures and the ability to connect technical data elements with business definitions.

SOFT SKILLS:

  • Effective Communication: Ability to clearly articulate technical findings and insights to both technical and non-technical stakeholders, including executives.
  • Problem-Solving: Demonstrated ability to approach challenges analytically and develop innovative solutions.
  • Collaboration: Comfortable working in a team environment with shifting priorities and deadlines.
  • Adaptability: Ability to multi-task and work independently in a fast-paced, dynamic environment.

WHO WE ARE:

TD is one of the world’s leading global financial institutions and is the fifth largest bank in North America by branches/stores. Every day, we deliver legendary customer experiences to over 27 million households and businesses in Canada, the United States and around the world. More than 95,000 TD colleagues bring their skills, talent, and creativity to the Bank, those we serve, and the economies we support. We are guided by our vision to Be the Better Bank and our purpose to enrich the lives of our customers, communities and colleagues.
TD is deeply committed to being a leader in customer experience, that is why we believe that all colleagues, no matter where they work, are customer facing. As we build our business and deliver on our strategy, we are innovating to enhance the customer experience and build capabilities to shape the future of banking. Whether you’ve got years of banking experience or are just starting your career in financial services, we can help you realize your potential. Through regular leadership and development conversations to mentorship and training programs, we’re here to support you towards your goals. As an organization, we keep growing – and so will you.

Responsibilities
  • Data Analysis & Insights: Analyze RESL data and provide performance insights on initiatives, using various statistical and analytical techniques, including but not limited to A/B testing, causal inference, and statistical modeling.
  • AIML Model Development : Design, develop, and deploy machine learning models, including supervised and unsupervised learning, reinforcement learning, and generative AI (e.g., large language models). Build and maintain model pipelines to ensure scalability and efficiency.
  • Model Explainability & Evaluation: Ensure model transparency by implementing explainability techniques and evaluating model performance using appropriate metrics.
  • Coding & Automation: Use SQL, Python, and PySpark to automate reporting processes, improve efficiency, and streamline workflows. Develop reusable code for data preprocessing, feature engineering, and model deployment.
  • Collaboration : Partner with SSF, RESL and Branch business partners, product owners, business management specialists, and technology teams to identify opportunities for AI/ML applications and ensure alignment with business objectives.
  • Presentation & Storytelling: Develop and maintain analysis reports, dashboards, and presentations. Communicate insights effectively to multiple business partners, both technical and non-technical, through compelling storytelling – verbally and in writing.
  • AI/ML Research & Innovation: Stay updated on the latest advancements in AI/ML, including generative AI, large language models, and statistical inferencing techniques. Apply innovative approaches to solve complex business problems.
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