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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

your main responsibilities will involve:,

• Lead discussions with the business stakeholders to identify, design and build suitable data solutions to solve business needs
• Deliver solutions using the latest techniques in data modelling, 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 modelling 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

Zurich Insurance is committed to being an equal opportunity employer. We aim to attract and retain the best qualified individuals available, without regard to criteria such as race/ethnicity, national origin, religion, gender, sexual orientation, age or disability