Data Scientist

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

Role Summary

Within Sun Life, the Data Science Chapter comprises 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 organization, the Data Science Chapter supports Canadian business units in their journey to leverage data and analytics as a foundational pillar in delivering business value.

Reporting to the Data Science Manager as a Data Scientist you will focus on supporting Canadian business units in accelerating the growth and application of advanced analytics in driving value. The 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 data and taking on challenging business problems. An inquisitive mind. Driven to ask questions to help lead projects to business value and not being afraid that the innovation attempts can and will lead to failing. A passion for solving problems. 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.

Key Responsibilities:

Data Science and Machine Learning

• Translate business goals into analytical problems; Identify optimal algorithms, statistical techniques, traditional ML suitable for the business problem at hand.
• Work in cross-functional teams to develop ML/data science products
• Apply best-in-breed data science techniques including descriptive, predictive, and machine learning methods from design to implementation
• Focus on feature engineering, model training and model evaluation
• Use AWS services including SageMaker, Lambda 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

Education & Experience

• Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Engineering, or related field (or equivalent experience)
• 1-2 years of experience developing and implementing data science solutions

Technical Skills

• Programming: Proficient in Python for data science and application development
• Data Engineering: Experience writing complex SQL and PySpark queries to extract and integrate data from multiple sources
• Statistical Knowledge: Solid understanding of hypothesis testing, causal inference, and model evaluation metrics
• Cloud Platform: Experience with AWS, particularly SageMaker for training and deploying ML models
• Machine Learning: Proficiency in supervised and unsupervised models
• Data Handling: Demonstrated experience in data transformation, manipulation, and working with structured vs. unstructured data
• Architecture: Strong understanding of APIs, microservices architecture, and cloud-native development

Core Competencies

• Exceptional communication skills to articulate complex technical concepts to both technical and non-technical audiences
• Effective oral and written storytelling and insights communication abilities
• Proven ability to manage multiple projects simultaneously with changing deadlines and priorities
• Strong problem-solving abilities and analytical skills with keen attention to detail

Preferred Qualifications

• Hands-on experience with GenAI frameworks and LLM APIs, including developing AI bots/agents with reasoning and tool-use capabilities
• Deep under