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Engineering Intern, NA Integrated Analytics (2027 Summer - New York)

Careerstore

New York · Posted Sep 14

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Location: New York, NY, US

Engineering Intern, NA Integrated Analytics (2027 Summer - New York)

Location:

New York, NY, US

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Job Type:

Full-Time

Work Mode:

Hybrid

Job Level:

Internship & Working Student

Job ID:

14243

Company:

Munich American Reassurance Company

Employment Type:

Temporary

Area of Expertise:

Engineering & Inspection

Description:

POSITION: Engineering Intern, NA Integrated Analytics (2027 Summer - New York)

LOCATION: New York, NY

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 internship 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

Note that this opportunity is open to current students who are returning to in-class studies upon the completion of the internship.

This role will be based in New York, NY. The base range for this internship will be $44 - $54 per hour. The hourly estimate displayed represents the typical hourly range for candidates hired in this position in New York. Factors that may be used to determine your actual rate will include your specific skills, level of schooling, exams, and how many years of experience.

You will be expected to relocate to the greater New York area, to meet our hybrid working model of at least 3 days a week in office. 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.

At Munich Re US, we see Diversity and Inclusion as a solution to the challenges and opportunities all around us. Our goal is to foster an inclusive culture and build a workforce that reflects the customers we serve and the communities in which we live and work. We strive to provide a workplace where all of our colleagues feel respected, valued and empowered to achieve their very best every day. We recruit and develop talent with a focus on pr

What they are looking for

Python Etl Rest Nlp Cloud

Details

Work type
Hybrid
Remote eligible
Yes

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