Senior Data Scientist

Job Description

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Reporting to the Director, Data Science, as a Senior Data Scientist you will focus on supporting Canadian business units in accelerating the growth and application of advanced analytics in driving value. The senior data scientist will leverage practical experience in applying varied data science techniques & offering advice/inputs to help with the design, development and implementation of analytics use cases.

What will you do?

Data Science and Machine Learning

• Translate business goals into analytical problems; Identify optimal algorithms, statistical techniques, traditional ML and/or GenAI architecture suitable for the business problem at hand.
• Work in cross-functional teams to develop ML/data science products, including GenAI applications
• Apply best-in-breed data science techniques including descriptive, predictive, and machine learning methods from design to implementation
• Focus on feature engineering, model training, model evaluation, and prompt engineering for LLMs
• Use AWS services including SageMaker, Lambda, Bedrock, and other AI/ML services
• Work with data warehousing, pipelines, and big data technologies such as AWS Glue for ETL, Glue Catalog, Glue Data Quality, and AWS Step Functions.

Technical Leadership & Collaboration

• Break down broader data science development milestones into actionable goals, activities, and work plans
• Create and maintain technical design artifacts describing application functionality, data models, interfaces, and integrations
• Engage and negotiate with stakeholders, make business recommendations with effective presentations of findings at multiple levels of stakeholders
• Champion continuous improvement and foster innovation within the analytics community

What will you need to succeed?

• Bachelor’s degree in computer science, Statistics, Mathematics, or related field, or equivalent experience
• 3+ years’ experience in developing and implementing data science techniques
• Proficient in Python for data science and GenAI application development
• Experience with writing complex SQL and PySpark queries to extract and integrate data from multiple database sources
• Proficiency in machine learning including supervised and unsupervised models
• Demonstrated experience in data transformation, data manipulation, and working with structured vs. unstructured data
• Strong understanding of APIs, microservices architecture, and cloud-native development
• Strong understanding of GenAI frameworks, LLM APIs, RAG techniques, prompt engineering, and fine-tuning methodologies along with familiarity with vector databases and embedding models