Applied Machine Learning Scientist II

This is a fully remote position, open to applicants in Canada.

📋 Description

• Offer technical proficiency while creating and executing cutting-edge machine learning models for personal banking services, covering areas such as marketing, risk management, and strategic optimization.

• Examine extensive and intricate structured and unstructured datasets that can scale to petabytes.

• Implement deep learning methodologies, including large language models, to formulate effective solutions.

• Execute feature engineering and selection from raw datasets to improve model precision and interpretability.

• Undertake research and assist in development initiatives.

• Prepare and present findings effectively.

• Update stakeholders on project status, plans, and potential risks.

• Cultivate relationships across various business divisions, corporate entities, and control functions.

• Ensure compliance with enterprise and regulatory standards.

• Generate and uphold necessary documentation.

• Oversee programs, policies, and practices to satisfy both business requirements and internal/external standards.

• Lead and execute actions and remediation strategies to tackle performance, risk, and governance challenges.

• Keep track of emerging issues, trends, and changing regulatory standards, evaluating their potential effects.

• Foster a culture of risk management and control that aligns with the organization's risk appetite.

• Serve as a brand ambassador for the business area and TD.

⛳️ Requirements

• Advanced degree (Master's or Ph.D.) in a STEM field—such as statistics, computer science, mathematics, physics, or engineering.

• Over 5 years of relevant professional experience.

• Experience in developing and deploying machine learning models for marketing applications like customer propensity, next best action, churn prediction, customer lifetime value, and audience targeting, showcasing measurable business impact.

• Familiarity with financial services, banking, retail, telecommunications, or digital marketing environments, including customer segmentation, campaign management, and personalization systems.

• Demonstrated expertise in the development and deployment of machine learning models in a production setting.

• Strong grasp of machine learning, deep learning, large language models, and traditional statistical methodologies.

• Proficient coding skills in Python, PySpark, PyTorch, and SQL.

• Experience with cloud computing platforms and MLOps methodologies.

• Excellent problem-solving capabilities.

• Proficient writing skills.

• Ability to convey complex ideas to non-technical audiences effectively.

🏝️ Benefits

• Competitive base salary.

• Variable compensation opportunities.

• Health and wellness benefits.

• Savings and retirement plans.

• Paid time off.

• Banking benefits and discounts.

• Opportunities for career advancement.

• Recognition and reward programs.

• Regular discussions regarding development.

• Access to training programs.

• Online learning resources.

• Mentorship initiatives.

• Comprehensive training and onboarding sessions.

• Interview accommodations, including accessible meeting rooms and captioning for virtual interviews.