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Munich Re

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

Toronto, ON, Canada

Pay: Compensation for this position ranges from $1,700 to $2,100 per week.
Posting language: English
Posted: Sep 28, 2026

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Original job 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:

https://www.munichre.com/us-life/en/digital-solutions.html

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:

Solid communication skills; spoken & written, formal/informal presentation;
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.

Please upload a copy of your unofficial transcript with your application package when applying for this position.

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 on 390 Bay St, and we operate in a hybrid work model.

Munich Re is currently operating under a hybrid working model, including a minimum of 3 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. If you receive a request for an interview and you have a disability which will require an accommodation to support your participation, please contact AODARequestHR@munichre.ca as soon as practical so that suitable accommodations can be arranged.

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More about this job

Responsibilities

The co-op will support the development of statistical, machine learning, and GenAI models to assist with underwriting, pricing, and claims management. They will also collaborate with cross-functional teams to implement solutions that improve operational quality and business decision-making.

Requirements

Candidates must be currently enrolled in an undergraduate or graduate program in Computer Science, Statistics, Data Science, or a related field. Proficiency in Python is required, along with strong communication skills and the ability to work with large, disparate datasets.

Skills

Python
SQL
R
Machine learning
Data science
Statistical modeling
GenAI
Data analysis
NLP
LLM APIs
Git
DevOps
Underwriting
Claims management
Communication skills

Benefits

Flexible remote/in-person work
Work-life balance
Mentorship
Leadership opportunities

Visa sponsorship

Not detected in the job text

Keywords

Data Science
Reinsurance
Machine Learning
GenAI
Python
SQL
R
Underwriting
Claims Management
NLP
LLM
DevOps
Git
Data Modeling
Analytics
Statistical Modeling
Insurance
Financial Services
Agentic LLM
Big Data

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