A NEW TRANSFORMATIONAL ADVENTURE AWAITS YOU…

How does 5 weeks of annual leave, a fulfilling career you’ll genuinely enjoy, and working for a reputable organization that promotes wellbeing and drives digital transformation sound to you?
As one of Forbes 2024 ‘World’s Best Employers’ and Fortune’s ‘World’s Most Admired Companies’ for 2025, Zurich - a leader in the insurance industry, is on a journey towards a brighter future… A brighter future for you - focused on your career, your wellbeing, and your community - as well as our customers and the planet.
Join us on this thrilling journey as we work towards our vision of becoming Australia’s leading digital insurer. If you’re eager to be part of a values-driven global organisation that’s experiencing real growth and transformation, and if you share our commitment to making a tangible difference and taking continuous steps towards a sustainable future for our people, customers, communities, and our planet, then keep reading!

LET’S CREATE A BRIGHTER FUTURE TOGETHER, LET’S MAKE A DIFFERENCE

It’s important to know, what you do matters. At Zurich, we don’t just cover, we care.
As a Senior Data Scientist within Zurich Life’s Data & Analytics team, you will play a pivotal role in shaping the future of AI-driven innovation across the business. Embedded in the AI Platforms team, you’ll be responsible for designing and delivering scalable, intelligent solutions that enhance operational efficiency and customer outcomes. This role offers the opportunity to work at the forefront of data science, applying advanced techniques in machine learning, NLP, and cloud-native technologies to solve complex business challenges.
You’ll collaborate closely with cross-functional teams and stakeholders to develop and deploy AI capabilities that integrate seamlessly into Zurich’s core data platforms. Your work will contribute directly to the strategic direction of our data and analytics initiatives, helping to build a resilient, insight-driven organisation.

You will also be responsible for the following:

• Build and optimize scalable Generative AI and machine learning solutions to automate workflows and deliver business value.
• Collaborate with cross-functional teams—including architects, engineers, and business stakeholders—to translate business requirements into practical, data-driven solutions.
• Apply advanced language modeling, NLP, and data extraction techniques to analyze unstructured data and generate actionable insights.
• Ensure all developed solutions meet high standards of scalability, reusability, and performance, proactively seeking opportunities for improvement and innovation.
• Uphold ethical data practices and ensure strict adherence to data privacy and governance requirements.

IMPORTANT TO YOUR SUCCESS – LET’S GROW TOGETHER

We’re looking for a strategic thought leader who can also be hands on when needed, with strong background in enterprise architecture and insurance transformation.

In order to be successful, you will have the following:

• 8–10 years of experience in data science, AI, or related fields, ideally within financial services or insurance.
• Strong proficiency in Python, with hands-on experience in model development, data manipulation, and API creation.
• Proven expertise in AWS tools including Sagemaker, Textract, Comprehend, and Lambda.
• Solid background in NLP and machine learning, with experience in language modeling and predictive analytics.
• Proven expertise in building GenAI solutions, especially Agentic AI solutions.
• Familiarity with Snowflake and cloud-based data warehousing is advantageous.

• Build and optimize scalable Generative AI and machine learning solutions to automate workflows and deliver business value.
• Collaborate with cross-functional teams—including architects, engineers, and business stakeholders—to translate business requirements into practical, data-driven solutions.
• Apply advanced language modeling, NLP, and data extraction techniques to analyze unstructured data and generate actionable insights.
• Ensure all developed solutions meet high standards of scalability, reusability, and performance, proactively seeking opportunities for improvement and innovation.
• Uphold ethical data practices and ensure strict adherence to data privacy and governance requirements