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Munich Re

Engineer, NA Integrated Analytics (2026 New Grad – New York)

Munich Re, New York, New York, us, 10261

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Overview

Munich Re, Canada (Life) – Location New York, United States POSITION: Engineer, NA Integrated Analytics (2026 New Grad – New York) LOCATION: New York, NY ANTICIPATED START DATE: 2026 (upon graduation) 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 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 & 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

Responsibilities

Contribute to various on-the-go projects, related to the following areas of concentration:

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

Participate in all stages of the software development lifecycle including QA and testing

Data Engineering: Build and expand our ETL batch and streaming pipelining practices

Manage and secure relational databases for complex data relations

DevOps: Containerize and deploy production applications on our Kubernetes cluster

Define, create, and build our CI/CD pipeline practices

Provision and manage enterprise cloud infrastructure via Infrastructure as Code

Manage and improve our observability stack

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

Understand and simplify our complex networking stance

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 Technical:

Undergraduate or Graduate degree in Computer Science, Engineering, Physics, Bioinformatics — or equivalent program

Familiarity with Python / other object-oriented language and software testing libraries (unittest / mock)

Familiarity with web app development using Flask, SQL and FastAPI

Knowledge of relational database systems (RDMS) and data management

Working knowledge of Linux commands

Ability to perform version control using Git and submit well-structured Pull Requests (PR)

Experience in creatively and rapidly debugging for on-the-job issues

Behavioral:

Solid communication skills; spoken and 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 independently research new tools and technologies

Preferred (but not required):

Familiarity with Azure or other cloud platforms and its related offerings

Exposure to authentication & authorization / networking / SQL ORM / PySpark / containerization / Kubernetes / Ansible / Terraform / Airflow / Databricks

Previous exposure to insurance or financial services environment

Note that this opportunity is open to both graduating students, as well as recent graduates who have obtained their degree within the past year.

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