Data Scientist

We’rebuilding AI products that move from promising prototypes to reliable, production-grade systems with measurable business impact. This role blends LLM application engineering, applied data science, and data engineering fundamentals.

You will own the end-to-end data operations lifecycle: sourcing and understanding data, designing scalable pipelines, enabling analytics and model development, and partnering with engineering and data science to productionize solutions. You will translate complex data into context for humans and AI applications, implement durable processes.

You’lldesign, evaluate, deploy, and continuously improve GenAI systems (RAG, agentic workflows, model fine-tuning) while helping shape the data foundation that makes them trustworthy at scale.

Position Responsibilities:

• 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 tovalidate,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).

Data acquisition & domain understanding

• 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.

Data engineering & platform delivery

• Design, build, andmaintainrobust 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.

Analytics, measurement & reporting

• Deliver ad-hoc analysis, business analytics, and reporting for projects of moderate scope/complexity.
• Define metrics andacquiredata 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.

Process design & operational excellence

• 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 andclosed-looplearning to continuously improve outcomes

Communication & mentorship

• Partner with Data Engineers, ML Engineers, BI, IT, and business leaders;participatein 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 andleveragesenior peers to accelerate delivery.

Required Qualifications:

Education & experience

• 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.

Technical skills

• Strong programming skills in Python; advanced SQLproficiency; 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

Analytics/ML foundations

• 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).

(Optional) Include with your application

• 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.
• We’llempower you to learn and grow the career you want.
• We’llrecognize and support you in a flexible environment where well-being and inclusion are more than just words.
• As part of our global team,we’llsupport you in shaping the future you want to see.

#LI-Hybrid

The role being advertised is an existing vacancy.

About Manulife and John Hancock

Manulife Financial Corporation is a leading international financial services provider, helping people make their decisions easier and lives better. To learn more about us, visit .

Manulife is an Equal Opportunity Employer

At Manulife/John Hancock, we embrace our diversity. We strive to attract, develop and retain a workforce that is as diverse as the customers we serve and to foster an inclusive work environment that embraces the strength of cultures and individuals. We are committed to fair recruitment, retention, advancement and compensation, and we administer all of our practices and programs without discrimination on the basis of race, ancestry, place of origin, colour, ethnic origin, citizenship, religion or religious beliefs, creed, sex (including pregnancy and pregnancy-related conditions), sexual orientation, genetic characteristics, veteran status, gender identity, gender expression, age, marital status, family status, disability, or any other ground protected by applicable law.

It is our priority to remove barriers to provide equal access to employment. A Human Resources representative will work with applicants who request a reasonable accommodation during the application process. All information shared during the accommodation request process will be stored and used in a manner that is consistent with applicable laws and Manulife/John Hancock policies. To request a reasonable accommodation in the application process, contact .

Referenced Salary Location

Toronto, Ontario

Working Arrangement

Hybrid

Salary range is expected to be between

$94,430.00 CAD - $144,430.00 CAD

Employees also have the opportunity to participate in incentive programs and earn incentive compensation tied to business and individual performance. The actual salary will vary depending on local market conditions, geography and relevant job-related factors such as knowledge, skills, qualifications, experience, and education/training. If you are applying for this role outside of the primary location, please contact for the salary range for your location.

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. If you are applying for this role in the U.S., please contact for more information about U.S.-specific paid time off provisions.

We use data and analytics technologies, such as artificial intelligence (AI), and automated processing tools, to analyze and process the information you provide to us or third parties in the application process. For more information, please refer to our .