Duration

• Summer 2026

The Position

You’ll work on exciting problems across analytics, machine learning, and generative AI that support Actuarial, Finance, Treasury, Risk, Compliance, and HR—examples include IFRS-17 analytics, liquidity and cash-forecasting, risk scenario testing, compliance/controls automation, and workforce insights.

Responsibilities

• Partner with Actuarial/Finance/Treasury/Risk/Compliance/HR to frame problems, success metrics, and deliverables.

• Explore and prepare data; engineer features and baselines; ensure data quality, lineage, and privacy.

• Build and evaluate ML models (GLM/GBM/XGBoost/NNs/time series) with sound experiment design and documentation.

• Prototype GenAI solutions (prompting, retrieval/RAG, evaluation) with a focus on safety, usefulness, and governance.

• Develop reproducible code and pipelines in Python/SQL (Spark/Databricks or equivalent) using Git and notebooks.

• Create clear visuals and narratives (dashboards, notebooks, concise write-ups) for mixed technical/non-technical audiences.

• Follow model governance and responsible-AI practices; present results, incorporate feedback, and iterate quickly.

Requirements

• Currently enrolled in a Master’s program (preferred) in Data/Computer Science, Statistics, Applied Math, Actuarial Science, Engineering, Finance/Economics, or related field; returning to studies after the work term.

• Hands-on experience from courses/research/internships building analytics or ML solutions.

• Proficiency in Python and SQL; familiarity with pandas/scikit-learn (and/or XGBoost) and solid EDA/statistics skills.

• Ability to write clean, reproducible code with Git; strong communication and collaboration skills.

• Work authorization for the hiring location for the duration of the co-op.

Nice To Haves

• Experience with Spark/Databricks, Azure cloud data platforms, and experiment tracking (e.g., MLflow).

• Exposure to GenAI/LLMs (RAG, prompt engineering, eval harnesses) and responsible-AI considerations.

• Domain interest/experience in one or more areas: IFRS-17/actuarial analytics, ALM/treasury, risk and stress testing, compliance and control testing, or HR/workforce analytics.

• Data visualization with Power BI or similar; confident presenting to stakeholders.

• (Nice to have) Actuarial exam progress (SOA/CAS) or finance credentials coursework (e.g., CFA), as applicable.

Company

Manulife Financial Corporation is a leading international financial services provider, helping people make their decisions easier and lives better.