Senior Data Scientist

Manulife • Toronto, ON

1d • CA$129,400 - CA$179,400 • Hybrid

About The Position

As a Senior Data Scientist supporting our Canadian AI team, you will play a key leadership role in developing analytics, machine learning, generative AI, and emerging agentic AI solutions that generate business insights, improve decision-making, and advance strategic priorities across the organization. You will lead and deliver complex data science initiatives, guide experimentation with new AI capabilities, and transform large, diverse datasets into actionable recommendations and scalable AI-enabled opportunities. Beyond technical expertise, you’ll mentor junior data scientists, champion best practices in Responsible AI and AI evaluation, and collaborate with business, product, engineering, and platform partners to drive meaningful business outcomes.

Requirements

• Advanced degree in Statistics, Mathematics, Computer Science, Engineering, Data Science, Artificial Intelligence, or related field; or Bachelor’s degree with equivalent technical experience.
• Minimum of 5 years of applicable experience in data science, advanced analytics, machine learning, or AI solution development.
• Advanced programming capability in Python, R, or similar analytical programming languages; strong SQL experience preferred.
• Advanced understanding of programming, statistics, machine learning, exploratory data analysis, data visualization, model production, insight generation, and data wrangling.
• Deep knowledge of statistical modeling, machine learning algorithms, experimental design, model evaluation, and analytical storytelling.
• Experience leading complex data science initiatives from discovery through implementation.
• Working knowledge of generative AI, LLMs, prompt engineering, embeddings, RAG, AI evaluation, or agentic AI concepts.
• Ability to influence stakeholders, develop business cases, and communicate complex technical concepts to senior audiences.
• Experience mentoring data scientists and promoting technical best practices.

Nice To Haves

• Experience with Azure, Databricks, Git, MLflow, model monitoring, or cloud-based AI/ML development environments.
• Familiarity with LLMOps, MLOps, model governance, Responsible AI, privacy, security, and model risk management.
• Experience with vector databases, semantic search, embeddings, RAG pipelines, or knowledge retrieval architectures.
• Exposure to LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI, or similar agentic AI frameworks.
• Experience supporting AI product development, experimentation portfolios, proof-of-concepts, MVPs, or scaled enterprise deployments.
• Experience in financial services, insurance, or another regulated environment.

Responsibilities

• Lead complex analytics, machine learning, and generative AI initiatives from problem framing through implementation.
• Define analytical approaches, model strategies, evaluation methods, and success measures for high-impact AI use cases.
• Guide experimentation with AI assistants, copilots, RAG solutions, and agentic workflows in partnership with Agentic Engineers and technology teams.
• Apply advanced statistical modeling, machine learning, experimentation, and AI evaluation techniques to solve business problems.
• Translate complex analytical findings and AI outputs into clear, implementable recommendations for business stakeholders and leaders.
• Prepare business cases for assigned initiatives, including expected benefits, adoption considerations, risks, and lessons learned from related business contexts.
• Develop an intimate understanding of supported business areas, including value chains, customer journeys, operating context, and company culture.
• Anticipate and proactively address peer review, governance, and model risk management considerations through clear documentation and defensible analytical choices.
• Provide guidance and mentorship to junior data scientists, facilitate best-practice exchange, and share technical expertise across the team.
• Contribute reusable approaches for experimentation, model validation, and AI solution assessment within assigned initiatives and the broader data science practice.
• Build a strong internal network across business, data science, engineering, platform, and governance partners, and share lessons learned to advance practice maturity.

Benefits

• health, dental, mental health, vision, short- and long-term disability, life and AD&D insurance coverage, adoption/surrogacy and wellness benefits, and employee/family assistance plans.
• various retirement savings plans (including pension and a global share ownership plan with employer matching contributions)
• financial education and counseling resources.
• generous paid time off program in Canada includes holidays, vacation, personal, and sick days, and we offer the full range of statutory leaves of absence.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior