Data Scientist

Sun Life

. Translate business goals into analytical problems and identify optimal algorithms, statistical techniques, and traditional machine learning methods .

Posted 9/24/2026full-timeToronto • CanadaJunior💰 CA$65,000 - CA$105,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Proficient in developing and implementing data science solutions using Python, SQL, and AWS services, with a strong focus on machine learning methodologies and data transformation. Capable of translating business goals into analytical frameworks while effectively communicating findings to stakeholders.

Highest-signal resume keywords

Python ProficiencyAWS SageMaker ExperienceSQL and PySpark ExpertiseMachine Learning Model EvaluationData Transformation and Manipulation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning MethodsFeature EngineeringModel TrainingModel Evaluation MetricsHypothesis TestingCausal InferenceSupervised and Unsupervised ModelsData Science Solutions DevelopmentAPIs and Microservices ArchitectureCloud-Native Development

Soft Skills

Exceptional CommunicationAnalytical SkillsProblem-SolvingAttention to DetailProject Management

Tools & Technologies

AWS GlueAWS LambdaAWS Step FunctionsGenAI FrameworksLLM APIsDockerCI/CD Concepts

Certifications & Qualifications

Bachelor's or Master's Degree in Statistics, Mathematics, Computer Science, Engineering, or Related FieldReliability Status Clearance

Industry Keywords

Data ScienceBig Data TechnologiesData WarehousingData PipelinesContinuous ImprovementInnovation in Analytics

Tech Stack

Tools & technologies

AWSCloudDockerMicroservicesPySparkPythonSQL

About the role

Key responsibilities & impact

Translate business goals into analytical problems and identify optimal algorithms, statistical techniques, and traditional machine learning methods
Work in cross-functional teams to develop machine learning and data science products
Apply descriptive, predictive, and machine learning methods from design through implementation
Perform 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 including AWS Glue, Glue Catalog, Glue Data Quality, and AWS Step Functions
Break down data science development milestones into actionable goals, activities, and work plans
Create and maintain technical design artifacts covering application functionality, data models, interfaces, and integrations
Engage and negotiate with stakeholders and make business recommendations through presentations of findings
Champion continuous improvement and foster innovation within the analytics community

Requirements

What you’ll need

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
Proficiency in Python for data science and application development
Experience writing complex SQL and PySpark queries
Solid understanding of hypothesis testing, causal inference, and model evaluation metrics
Experience with AWS, particularly SageMaker for training and deploying ML models
Proficiency in supervised and unsupervised models
Experience in data transformation, manipulation, and working with structured and unstructured data
Strong understanding of APIs, microservices architecture, and cloud-native development
Exceptional communication and storytelling abilities
Ability to manage multiple projects with changing deadlines and priorities
Strong problem-solving, analytical, and attention-to-detail skills
Reliability Status Clearance required before employment
Ability to satisfactorily complete applicable background checks before starting and during employment
Preferred: hands-on experience with GenAI frameworks and LLM APIs, including AI bots/agents with reasoning and tool-use capabilities
Preferred: understanding of RAG techniques, prompt engineering, and fine-tuning methodologies
Preferred: familiarity with vector databases and embedding models
Preferred: experience with Docker and CI/CD concepts

Benefits

Comp & perks

Wellness programs supporting mental, physical, and financial health
Variety of career paths and networking opportunities
Hybrid work flexibility between home and office
Incentive plans for eligible employees, subject to individual and company performance
Accommodation available for applicants with disabilities
Alternative-format job postings available upon request