Reporting to the Director, Data Science, focus on supporting Canadian business units in accelerating the growth and application of advanced analytics
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
Engage and negotiate with stakeholders and make business recommendations
Requirements
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