Data Science Co-op, NA Integrated Analytics (2027 Summer - Toronto)

InternHunt; Toronto; Hybrid; CAD 77,000 - 96,000; Part time

Job summary

Munich Re is hiring a Data Science Co-op for the NA Integrated Analytics team in Toronto for Summer 2027. The role involves developing ML and GenAI solutions for underwriting, pricing, and claims, with collaboration across the company and mentors from leadership.

The position is hybrid, requiring relocation to Toronto and at least 3 days in office per week. The co-op offers hands-on experience across reinsurance analytics, exposure to leadership, and opportunities to grow into a data science

Qualifications

• Undergrad/Grad degree in Computer Science, Statistics, Data Science/Analytics, Applied Mathematics, Engineering or equivalent.
• Comfortable working with varied data sources and data manipulation at scale.
• Experience with analytics across the modeling lifecycle: data gathering, design, testing, implementation, communication.
• Familiarity with Python (required); exposure to SQL or R is a plus.

Responsibilities

• Support development of statistical, ML, and GenAI techniques for underwriting, pricing and claims models.
• Build and implement solutions to improve core processes and enable revenue growth or cost savings.
• Research new data modeling approaches to unlock actionable insights.
• Collaborate with Munich Re functions to inform business decisions.
• Network with existing data science groups within Munich Re.

Skills

Communication

Teamwork

Adaptability

Education

CS/Statistics/Data Science/Analytics/Engineering degree

Large datasets coursework

Tools

Python

SQL

R

Git

Claude Code

Codex

Job description

Data Science Co-op, NA Integrated Analytics (2027 Summer - Toronto)

2026-09-29

Role Description

POSITION:Data Science Co-op, NA Integrated Analytics (2027 Summer - Toronto)

LOCATION:Toronto, ON

ANTICIPATED START DATE:Summer 2027

Together, we engage with everything we have and are, to help humankind act braver and better. As the world’s leading reinsurance company with more than 40,000 employees in over 50 locations around the globe, Munich Re introduces a paradigm shift in the way you think about insurance. By turning uncertainty into manageable risk, we enable fundamental change. We recognize Diversity, Inclusion, and Belonging as a key priority with a culture that welcomes different thoughts and opinions. We dare to think big and are continuously innovating on behalf of our clients.

How can AI promote longer and healthier lives? Armed with decades of risk data, novel data sources, and a team of innovative data scientists, engineers, and domain experts, Munich Re is building solutions that are transforming the life insurance industry.

• Develop solutions that allow easier access to insurance and healthier lifestyles
• Build highly scalable products with best security, ML, DevOps practices
• Research bias and fairness, disease models, NLP, agentic LLM solutions & more
• Discover diverse careers with leadership opportunities
• Flexible remote/in-person work + focus on work-life balance
• Be part of a fast-growing team that values transparency & diversity

To learn more about the North American Integrated Analytics team, please visit our site:

Our co-op placements provide you with an excellent opportunity to practically apply your classroom and technical training in the reinsurance industry. While with our team, you’ll be; coached by experienced industry professionals, exposed to Munich Re leadership, challenged as a valuable team member and contributor doing meaningful work, and mentored to develop a solid foundation that will help position you as a future leader in the field.

Position Overview:Responsibilities may include, but will not be limited to the following:

• Supporting the development of statistical, machine learning, and GenAI techniques to assist with building models for underwriting, pricing, and claims management;
• Assist in building and implementing solutions that enable operational units to improve quality and speed of core processes in order to generate incremental revenue or reduce expense;
• Help research new ways of modeling data to unlock actionable insights or improve processes;
• Collaborate across Munich Re functions to understand how analytics can influence business decisions;
• Network with existing data science groups at Munich Re.

Qualifications:We’re looking for well‑rounded individuals who are technically astute, have strong communication skills, and demonstrate the ability to build positive relationships with internal clients. We’re seeking energetic and collaborative professionals who are excited to join our winning team and show promise of becoming a future leader in the data science space.

Specifically, we’re looking for the following qualifications:

Technical:

• Undergraduate or Graduate degree in Computer Science, Statistics, Data Science/Analytics, Applied Mathematics, Engineering (Physics, Bioinformatics) – or equivalent program offering coursework manipulating large datasets;
• Comfortable working with and combining disparate and varied data sources;
• Familiarity working with analytics through the modeling lifecycle including gathering data, design, recommendations, testing, implementation, communication, and revisions;
• Experience working with any of the following: python, SQL, or R (familiarity with python is required, and multiple languages considered an asset).

Behavioral:

• Resourceful and able to learn quickly;
• Proven ability to thrive in a dynamic environment.

Preferred (but not required):

• Experience using git and an AI coding tool such as Claude Code or Codex;
• Experience working with LLM APIs and/or building agents
• Previous exposure to insurance or financial services environment is preferred but not required.

Note that this opportunity is open to current students who are returning to in‑class studies upon the completion of their co‑op.

Compensation for this position ranges from $1,700 to $2,100 per week. This range represents the typical compensation for candidates hired into this role.

This role is located in our Toronto office on390 Bay St, and we operate in ahybrid work model.

Munich Re is currently operating under a hybrid working model, including a minimum of3 days in office per week. Students are expected to relocate to the city in which they work for the duration of their co‑op, so they can fully benefit from the full program integration. This provides a great opportunity to network, develop soft skills and become immersed within the greater Munich Re culture; including engaging with your team while in‑office for face‑to‑face meetings, sharing meaningful moments, and allocating time to connect with your Manager.

Please note that only candidates who are selected for interview will be contacted directly. We thank all candidates for their interest.

Munich Re is committed to providing a work environment that is inclusive and free of employment barriers and discrimination.

Accommodations will be made for qualified applicants with a disability throughout the recruitment process.