Senior Data Scientist Job Toronto area,Ontario Canada,IT/Tech

Job Description

Role Summary

Within Sun Life, the Data and Analytics COE 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 Data and Analytics COE organization, the Data Science COE 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, 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.

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.

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; working with structured data and unstructured data.
Thirst for learning. You are a data scientist who is constantly updating their knowledge of data science state-of-the-art.

What you will do:

Data Science and Machine Learning

Translate business goals into analytical problems;
Identify optimal algorithms, statistical techniques 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

GenAI & Agentic AI Development

Design, develop, and deploy GenAI solutions including AI agents, chatbots, and autonomous systems that solve complex business problems

Research and pilot the latest GenAI technologies, RAG (Retrieval-Augmented Generation) techniques, and agentic frameworks (Lang Chain, Lang Graph, CrewAI etc.)

Implement AI bots/agents with advanced reasoning capabilities and tool use patterns

Work with vector databases and embedding models to build intelligent information retrieval systems

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 you need to succeed:

Bachelor's degree in Computer Science, Statistics, Mathematics, or related field, or equivalent experience

5+ 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

Hands-on expertise with GenAI frameworks and LLM APIs with experience developing AI bots/agents with reasoning and tool-use capabilities

Strong understanding of RAG techniques, prompt engineering, and fine-tuning methodologies and familiarity with vector databases and embedding models

Experience with chatbot development concepts and conversational AI design

Exceptional communication skills to articulate…