About The Team: 

This role is within the Data Driven Underwriting (DDUW) Solutions Americas team under Swiss re L&H Solutions division. You will be joining the DDUW product team who is on a mission to create a best-in-class solution in underwriting for Life Insurance carriers to address the current industry pain points with disparate data sources in the US market. The team has diverse skillsets of experts from underwriting, and technology and the team work collaboratively with cross functional delivery teams across the globe. 

About The Role: 

As a Machine learning Engineering Intern, you will join a Product team of software engineers, underwriting experts and business leaders to work on a global strategic initiative to make better use of our data and enhance our ability to make data driven decisions. You will work closely with business partners to find opportunities for leveraging data to drive business solutions, understand the business problem and extract relevant trends and patterns from data. 

You will also support the Analytics reporting tool creation which directly drives product insights. 

About You: 

Are you eager to disrupt the insurance industry with us and make an impact? Do you wish to have your talent recognized and rewarded? Then join our internal start-up squad and find an encouraging environment in which we aspire for client delight and make it happen for Solutions! 

• Currently enrolled in an accredited program at a college or university with a focus on data science/analytics, computer science, computational linguistics or related field. 

• Must be available for the Summer 2024 term (May - Aug) 

• Strong communication and teamwork skills 

• Exposure or experience in areas such as information retrieval, natural language processing, data analytics and information visualization. 

• Basic understanding of statistical analysis. 

• Ability to adapt to a flexible work environment. 

• Standout colleague with a "can do" attitude. 

• Exceptional academic performance (minimum 3.25 GPA) 

Position Requirements: 

• Strong background in Computer Science.  

• Min. 3 years of work experience. 

• Deep knowledge of LLMs, Natural Language Understanding 

• Proficiency in programming languages such as Python or R, as well as experience with frameworks such as Tensorflow, PyTorch etc. 

• Experience in the chatbot or conversational AI industry is a plus 

Opportunities: 

• Build prototypes, run experiments, train new models, and support developing data science products that solve real-world business problems 

• Put AI and chat bot build knowledge to enhance product offering to use on real products. 

• Communicate findings that help support solving business problems, insight generation and decision making 

• Develop custom data models and algorithms to apply to datasets 

• Build end to end big data pipelines from data ingestion to insight generation 

• Check to ensure consistency, integrity and robustness of data pipelines 

• Manage code base and git repository in the development platform 

About Swiss Re

Swiss Re is one of the world’s leading providers of reinsurance, insurance and other forms of insurance-based risk transfer, working to make the world more resilient. We anticipate and manage a wide variety of risks, from natural catastrophes and climate change to cybercrime. We cover both Property & Casualty and Life & Health. Combining experience with creative thinking and cutting-edge expertise, we create new opportunities and solutions for our clients. This is possible thanks to the collaboration of more than 14,000 employees across the world.

Our success depends on our ability to build an inclusive culture encouraging fresh perspectives and innovative thinking. We embrace a workplace where everyone has equal opportunities to thrive and develop professionally regardless of their age, gender, race, ethnicity, gender identity and/or expression, sexual orientation, physical or mental ability, skillset, thought or other characteristics. In our inclusive and flexible environment everyone can bring their authentic selves to work and their passion for sustainability.