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

Standort Toronto, Kanada Art der Arbeit Vollzeit Arbeitsform Hybrid Job level Praktikanten & Werkstudenten Job ID 14379 Unternehmen Munich Re, Canada (Life) Anstellungsart Befristet Fachbereich Daten, BI und Analytik

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POSITION: Engineering 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 ML promote longer and healthier lives? Armed with decades of risk data, novel data sources, and a team of innovative 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 & 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:

• Contribute to various on-the-go projects, related to the following areas of concentration (as needed and as fits with your focus):

• Create, test and support the development of Python based applications and predictive models deployed as RESTful microservices APIs

• Build and expand our ETL pipelining practices to ease the flow of data into our cloud infrastructure

• Deploy, monitor and improve visibility for our production applications

• Integrate security into all stages of the engineering pipeline and employ a “security first” attitude

• Build data products with heavy reliance on cloud infrastructure

• Incorporate Git, testing, CI/CD workflows and PRs into any coding project

• Participate in various research projects in the field of machine learning and deep learning – collaborating with our greater team of scientists and engineers.

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 engineering space.

Specifically, we’re looking for the following qualifications:

Technical:

• Undergraduate or Graduate degree in Computer Science, Engineering, Physics, Bioinformatics – or equivalent program;
• Familiarity with Python or other object-oriented languages;
• Experience developing software using principles from the software design life cycle; Proficiency with agentic coding

Behavioral:

• Solid communication skills; spoken & written, formal/informal presentation;
• Able to learn quickly and independently and motivated to help others;
• Proven ability to thrive in a dynamic environment; Ability to creatively and rapidly problem solve for on-the-job issues.

Preferred (but not required):

• Familiarity with Azure or other cloud platforms;
• Ability to independently research new tools and technologies;
• Previous exposure to insurance or financial services environment;
• Experience in Terraform, Kubernetes, Helm
• Interest in full-stack development

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 [email protected] as soon as practical so that suitable accommodations can be arranged.

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