Senior Data Scientist

at  Sun Life

You are as unique as your background, experience and point of view. Here, you’ll be encouraged, empowered and challenged to be your best self. You’ll work with dynamic colleagues - experts in their fields - who are eager to share their knowledge with you. Your leaders will inspire and help you reach your potential and soar to new heights. Every day, you’ll have new and exciting opportunities to make life brighter for our Clients - who are at the heart of everything we do. Discover how you can make a difference in the lives of individuals, families and communities around the world.

JOB DESCRIPTION:

Within Sun Life, the Analytics & Insights teams are comprised of savvy and intellectually curious professionals who are on a mission to transform how we apply data and analytics to support Sun Life becoming client centric. An integral part of the Analytics & Insights organization, the Data Science team supports Canadian business units in their journey to leverage data and analytics as a foundational pillar in delivering business value.
Reporting to the Director, Data Science CoE, as a Senior Data Scientist you will focus on supporting Canadian business units in accelerating the growth and application of 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.

UNIQUE REQUIREMENTS

The candidate selected for this role is required to have special clearance from the Royal Canadian Mounted Police. To see if you are eligible for this clearance, please review the section 201 on the Federal Government site (http://iss-ssi.pwgsc-tpsgc.gc.ca/msi-ism/ch2-prt1-eng.html)
Must be able to attain Canadian Reliability Security Clearance (administered by submitting fingerprints to the RCMP, who then conduct min. 5 year history checks)

Technical skills in both data and computer science. There are 3 core technical skills we look for:

• in-depth coding knowledge of an analytical tool(s) (i.e., Python)
• data science techniques and concepts
• Hand-on experience with NLP, deep learning, GenAI, and LLM

SUN LIFE VIEWS SUCCESS IN THIS ROLE IN DEMONSTRATION OF THESE KEY ATTRIBUTES:

Fierce curiosity. You are drawn to discovering and leveraging new data and taking on challenging business puzzles.
An inquisitive mind. Driven to ask questions to help lead projects to commercial value and not being afraid that the innovation attempts can and will lead to failing.
A passion for solving problems. The most successful data scientists’ solution for what the right data to use, they solve using the most suitable (not most advanced) algorithms for the problem at hand and figure out how to execute and deliver with highest efficiency.
Thirst for learning. You are a data scientist who is constantly updating their knowledge of data science state-of-the-art.

Technical skills in both data and computer science. There are 3 core technical skills we look for:

• in-depth coding knowledge of an analytical tool(s) (i.e., Python)
• data science techniques and concepts
• Hand-on experience with NLP, deep learning, GenAI, and LLMs

WHAT WILL YOU DO?

• Serve as the product owner for Canada’s GenAI squad MLOps framework, standards, and guidelines, and fostering a community around it.
• Lead the development of custom ML, Gen AI, NLP, LLM Models for batch and stream processing-based AI ML pipelines. Model components will include data ingestion, preprocessing, search and retrieval, Retrieval Augmented Generation (RAG), NLP/LLM model development, fine-tuning and prompt engineering.
• Conduct rigorous model evaluation and validation to ensure high performance, accuracy, consistency, and reliability. Optimize models for improved system efficiency.
• Deploy production-ready models in collaboration with MLOps team, ensuring reliability, scalability and smooth integration.
• Lead cross-functional agile teams to break down data science projects into milestones, activities and work plans.
• Collaborate closely with product, engineering and business teams throughout the full product development lifecycle.
• Establish and enforce best practices and governance standards for responsible ML development.
• Troubleshoot complex issues and develop innovative solutions related to models, data and pipelines.
• Mentor and guide more junior data scientists.