Manulife is a leading international financial services provider, and they are seeking a Data Scientist to help build AI products that transition from prototypes to production-grade systems. The role involves owning the end-to-end data operations lifecycle, designing scalable pipelines, and collaborating with engineering and data science teams to productionize solutions.
Design, evaluate, and deploy RAG pipelines, agentic systems, and chat interfaces, including advanced retrieval methods and modular designs
Conduct LLM red-teaming, bias detection, and alignment testing; build automated evaluation frameworks and develop measurement/feedback loops
GenAI engineering in the Azure ecosystem: integrate and test LLMs using OpenAI APIs, Azure AI Services, Azure AI Search/Cognitive Search, Azure ML, Databricks, and (where applicable) AKS/Kubernetes
Develop and implement ML models (traditional + GenAI) and design/execute experiments to validate, optimize, and scale solutions
Contribute to fine-tuning and pre-training pipelines for domain use cases; use synthetic data generation and creative data sourcing to improve modeling outcomes (including sparse/rare-event problems)
Identify, evaluate, and obtain access to internal and external data sources with minimal guidance
Partner with subject matter experts to understand data definitions, quality, lineage, and business context
Document datasets using standard templates (metadata, assumptions, refresh cadence, known issues) and present findings to stakeholders
Design, build, and maintain robust ETL/ELT pipelines to extract, transform, and stage data for AI/ML and BI consumption
Create and manage tables, schemas, and databases; implement data models that support analytics and machine learning use cases
Productionize pipelines and datasets with monitoring, alerting, data quality checks, and performance tuning
Collaborate with internal/external engineers and data scientists to integrate data science solutions into production systems
Deliver ad-hoc analysis, business analytics, and reporting for projects of moderate scope/complexity
Define metrics and acquire data to measure solution effectiveness; communicate results and recommendations to peers and stakeholders
Build dashboards and reporting assets (e.g., Tableau/Power BI/Qlik) to support decision-making
Help design scalable operating processes to implement analytics/AI insights, including: Clear roles and responsibilities across partners, Defined workflows, system/data flows, and contingencies, Checks-and-balances (validation, QA, approvals), KPI tracking and closed-loop learning to continuously improve outcomes
Partner with Data Engineers, ML Engineers, BI, IT, and business leaders; participate in code/model reviews, documentation, agile delivery, and mentorship
Communicate moderately complex technical and analytical topics to senior team members and business partners
Build a strong internal network and leverage senior peers to accelerate delivery
Qualification
Required
Bachelor's degree in Computer Science, Engineering, Math, or equivalent practical experience
2+ years of relevant experience in data engineering, analytics engineering, or BI/analytics roles supporting AI/ML or advanced analytics
Advanced degree (MS/PhD) in a quantitative field or equivalent depth through impactful work; publications or research contributions are a plus
Strong programming skills in Python; advanced SQL proficiency; Java experience is asset
Advanced experience with data transformation and modeling for analytics/BI and ML feature readiness
Strong understanding of relational databases and data modeling concepts
Working knowledge of distributed computing concepts/tools
Advanced experience with data visualization tools
Ability to explore and mine large structured and unstructured datasets using a systematic approach
Familiarity with statistics and common analytical techniques (e.g., regression, clustering, PCA, decision trees, survival analysis)
Basic understanding of machine learning algorithms and familiarity with common AI/ML toolkits
Hands-on experience with RAG, embeddings, semantic search, and vector databases (e.g., FAISS, MongoDB, Neo4j) and/or graph-based analytics
Knowledge of GenAI frameworks such as LangChain, Semantic Kernel, and agent frameworks (e.g., Autogen / LangGraph / CrewAI-style tools)
Preferred
1–2 examples of work (GitHub, write-ups, papers, demos, etc.) showing: something you built end-to-end, how you evaluated quality and failure modes, and how you iterated based on evidence and constraints
Benefits
Employees also have the opportunity to participate in incentive programs and earn incentive compensation tied to business and individual performance.
Manulife offers eligible employees a wide array of customizable benefits, including 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.
We also offer eligible employees various retirement savings plans (including pension and a global share ownership plan with employer matching contributions) and financial education and counseling resources.
Our 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.
Manulife is a leading international financial services group that helps people make their decisions easier and lives better.
