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About the Role
Scotiabank is seeking a specialized Data Scientist to join the Global Artificial Intelligence and Machine Learning team. This role focuses on building and deploying AI/ML products using Large Language Models (LLMs) to transform document processing and value extraction. The ideal candidate will contribute to the bank's AI/ML strategy by solving high-impact business challenges with Gemini prompting and Python coding, requiring strong communication, collaboration, and stakeholder engagement skills.
Responsibilities
- Develop, test, and implement highly effective models optimized for specific document understanding tasks.
- Write and maintain high-quality Python code to preprocess, process, and analyze large volumes of structured and unstructured documents, building robust data pipelines.
- Design, build, and rigorously evaluate specialized machine learning models for document understanding, ensuring accuracy, fairness, and scalability.
- Collaborate with Data Engineers and Software Developers to develop and deploy document understanding solutions efficiently and reliably into production environments.
- Stay up to date on the latest advances in generative AI, Python coding libraries, machine learning best practices, and the field of Document AI.
- Support Research & Development initiatives focused on applying design thinking and advanced AI/ML techniques to solve business challenges.
- Support high-impact analytical use cases across a diverse set of business lines, delivering AI/ML products that create value for both customers and the organization.
- Collaborate with key stakeholders and partners to define, promote, and enforce machine learning and artificial intelligence best practices across the organization.
- Understand how the Bank’s risk appetite and risk culture should be considered in decision-making related to model development and deployment.
- Work seamlessly with Data Scientists, Data Engineers, Software Engineers, and AI/ML Product Managers to implement scalable AI/ML solutions across the bank.
- Communicate project progress, technical concepts, and business value clearly to both technical and non-technical stakeholders.
Requirements
- Expert-level proficiency in Python for data manipulation, statistical modeling, and pipeline development.
- Proven, hands-on experience designing and optimizing prompts for advanced Large Language Models (specifically Gemini or comparable LLMs) tailored for structured document analysis.
- Direct experience with document understanding tasks, including working with unstructured text, OCR output, and information extraction from complex forms, records, or contracts.
- Practical experience with ML/AI techniques, including supervised learning, unsupervised learning, deep learning, and Natural Language Processing (NLP).
- Experience with big data tools and technologies such as SQL, Hadoop, and Spark.
- Proven ability to ingest, clean, and work effectively with large volumes of structured and unstructured data.
- Experience with DevOps principles and software engineering best practices, including Git, CI/CD pipelines, and Agile delivery methodologies.
- Effective communication skills with the ability to prepare clear project documentation and deliver compelling presentations.
- Ability to translate complex technical concepts into tangible business value and collaborate effectively across technical and non-technical teams.
- Working knowledge of visualization and reporting tools such as Power BI.
- Strong communication and stakeholder management skills, with the ability to clearly articulate complex technical concepts to both technical and non-technical audiences and build effective working relationships across the organization.
Skills
- Python
- Large Language Models (LLMs)
- Gemini prompting
- Document AI
- Machine Learning
- Natural Language Processing (NLP)
- SQL
- Hadoop
- Spark
- DevOps
- Git
- CI/CD
- Agile
- Power BI
Location
- Canada : Ontario : Toronto
Work Type
- Full-time
Experience Level
- Expert-level proficiency in Python
- Proven, hands-on experience with LLMs
- Direct experience with document understanding tasks
- Practical experience with ML/AI techniques
- Experience with big data tools
- Experience with DevOps principles
- Experience with software engineering best practices
Education Level
- University degree or postgraduate degree in a STEM discipline (Science, Technology, Engineering, Mathematics, Statistics, Computer Science, or a related field).
About the Company
- Scotiabank is a leading bank in the Americas.
- Guided by our purpose: "for every future", we help our customers, their families and their communities achieve success through a broad range of advice, products and services, including personal and commercial banking, wealth management and private banking, corporate and investment banking, and capital markets.
Equal Opportunity
- At Scotiabank, we value the unique skills and experiences each individual brings to the Bank, and are committed to creating and maintaining an inclusive and accessible environment for everyone.
- If you require accommodation (including, but not limited to, an accessible interview site, alternate format documents, ASL Interpreter, or Assistive Technology) during the recruitment and selection process, please let our Recruitment team know.