Data Scientist

Allianz

Allianz, a leading global brand in insurance and asset management, is celebrated as one of Australia's Best Workplaces for 2024. The company emphasizes an inclusive culture, promoting diversity and lifelong learning. The Data Scientist role is crucial in deploying AI and Machine Learning for business transformation and value.

In this role you can expect to have the responsibilities:

• Analyze large structured and unstructured datasets to identify trends and patterns.
• Develop predictive models and machine-learning algorithms.
• Implement modeling solutions into operations, ensuring quality through testing and quality assurance.
• Create training and user documentation for models.
• Collaborate across functions to address business problems with data-driven solutions.
• Mentor and inspire the team and business about data science best practices.
• Work with Data Office teams for delivering advanced analytics solutions.

This role comes with the following benefits:

• Inclusive culture with a focus on customer outcomes.
• Flexible work-life balance with remote work options.
• Career development through mentoring and access to learning resources.
• Financial perks, including product discounts and an Employee Share Purchase Program.

This role requires you to have:

• Degree in Computer Science, Mathematics, Statistics, or a related field.
• Experience in a Data Scientist role solving commercial problems with data science.
• Proficiency in data mining, statistical methods, and machine-learning techniques.
• Programming experience with R, Python, or SQL.
• Ability to understand complexity and offer practical solutions.
• Strong relationship-building skills and stakeholder management.
• Exceptional communication skills with the ability to influence various audiences.
• Effective planning, task organization, and resource management.

You would benefit from having:

Allianz values diversity and inclusion, fostering an equitable workplace environment. The company supports adjustments for inclusivity in recruitment processes.