Data Science Intern
Zurich Insurance
Job Overview
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Job Description
Who we are
Zurich is a leading multi-line insurer serving people and businesses in more than 200 countries and territories for more than 150 years. Today, we help communities stay resilient in the face of an ever-changing risk landscape, whether driven by climate change or the effects of technology on work and the way we live our lives. In an era of unprecedented change, we are determined to shape a future in which we can all thrive. Reflecting its purpose to ‘create a brighter future together,’ Zurich aspires to be one of the most responsible and impactful businesses in the world.
Our Opportunity
The regional Data and Analytics team at Zurich Insurance is at the heart of driving innovation across our business units, championing AI adoption and data maturity throughout the APAC region. As a Data Science Intern, you’ll join a dynamic, collaborative team that thrives on solving real-world challenges and making a measurable impact. You’ll have the opportunity to work directly with stakeholders, supporting the delivery of cutting-edge AI and analytical solutions using the latest data science and engineering practices. As part of our agile and lean team, you’ll help design and implement solutions that shape the future of our business—making every day a chance to learn, grow, and contribute to our shared success.
Your Role as a Data Science Intern
As a Data Science Intern, your main responsibilities will involve:
- Lead discussions with business stakeholders to identify, design and build suitable data solutions to solve business needs.
- Deliver solutions using the latest techniques in data modeling, machine learning, NLP, Computer Vision, and Gen AI.
- Lead the end-to-end implementation of data initiatives to improve customer engagement, business processes and product enhancements through automation and actionable insights.
- Analyze and review complex data from multiple internal and external sources to make informed, authoritative recommendations to improve business performance in the medium and longer term.
- Engage with stakeholders to increase awareness and adoption of the solutions you build.
Your Skills And Experience
As a Data Science Intern, your skills and qualifications will ideally include:
- A bachelor’s degree (or working towards one) in computer science, math, data science or other relevant subjects.
- Ability to lead and implement data science projects to deliver measurable benefits.
- Knowledge of statistical and predictive modeling techniques such as machine learning, decision trees, probability networks, clustering, neural networks, LLMs and more.
- Experience in managing structured and unstructured data, including free text, images, web data and more.
- Well versed in building on the cloud, best practices and languages such as Python.
- Past data science projects delivered is a plus.
Period of Internship
4-6 months
Key skills/competency
- Data Science
- Machine Learning
- Natural Language Processing (NLP)
- Computer Vision
- Generative AI
- Python
- Cloud Platforms
- Statistical Modeling
- Data Analysis
- Stakeholder Engagement
How to Get Hired at Zurich Insurance
- Research Zurich Insurance's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor, focusing on their commitment to innovation and inclusion.
- Tailor your resume effectively: Highlight specific data science projects, demonstrable machine learning skills, cloud platform experience, and your ability to deliver measurable benefits to optimize for Zurich Insurance.
- Showcase problem-solving aptitude: Prepare clear, concise examples illustrating how you've used data science to identify, design, and implement solutions for business challenges in past experiences.
- Demonstrate passion for AI & Data: Articulate your interest in advanced topics like Generative AI, NLP, Computer Vision, and how these can shape the future of insurance at Zurich Insurance.
- Network strategically: Connect with current Zurich Insurance data and analytics professionals on LinkedIn to gain deeper insights into the team's work and culture.
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