Data analytics specialist/Machine learning | NSW - Sydney

Job reference number: ALL/EX/1408058

When you work at Allianz, you're part of a strong global insurer, helping to protect over 3 million Australians. We value diverse thinking, so your ideas and innovative mindset will be warmly welcomed. You'll experience a friendly environment working with talented people, where you'll be included and have your capabilities recognised. And you'll be supported to reach your full potential and enjoy an enriching career.

Due to business growth and demand, our Technical division is currently seeking to appoint a Data analytics specialist/Machine learning to join our Actuarial Pricing & Data Analytics team based at our Market Street, Sydney CBD office. This is an excellent opportunity to utilise your data science, problem solving, communication and analytical skills.

The key responsibility of the Data analytics specialist/Machine learning is to establish the data analytics best practice and drive the embedment across pricing and portfolio management activities within the Technical Division. This role will provide data science and analytics expertise and develop best practice framework which will be implemented consistently across the pricing and portfolio management activities for all products.

In addition, you will work closely with ‎internal stakeholders within the business to provide ‎innovative solutions to our customers.‎  As a member of the Technical Division you will be responsible for developing insights that directly drive business outcomes.

Key role responsibilities: 

  • Develop data analytics strategy for the Actuarial Pricing teams to strengthen our data analytics and actuarial pricing capabilities
  • Lead data analytics projects and develop best practice frameworks for the Actuarial Pricing teams
  • Develop and deploy data science/machine learning solutions within the pricing and portfolio management framework to achieve Technical Excellence
  • Support implementation and embedment of data analytics best practice across the pricing and portfolio management activities
  • Provide expert advice and guidance to pricing analysts
  • Apply innovative thinking in solving customer problems, utilising big data and advanced analytics
  • Collaborate with internal stakeholders on enterprise data initiatives and liaise with Allianz Group to leverage existing materials and development
  • Share knowledge on advanced analytics techniques and best practice framework with the Actuarial Pricing team

 About You:

The successful applicant will possess the following experience within a similar Data Science or Actuarial role, with an understanding of General Insurance products. 

  • Minimum 5 years' experience in data science and analytics, with experience in General insurance pricing desirable
  • Experience in predictive modelling (such as claims, quote conversion, customer retention) with Machine Learning techniques
  • Experience with project management is beneficial, including the ability to lead and coach others
  • Strong “first principles” problem-solving skills, be curious and creative
  • Strong consulting and influencing skills, the ability to co-create strategy and valuable analytical solutions with key business stakeholders
  • Demonstrated ability in innovative development practices, be able to rapidly generate data science prototypes using relevant techniques
  • Not satisfied with the status quo, with a proven ability to deliver projects on time, by identifying and removing blockers along the way
  • Data Science or Actuarial Qualification would be viewed favourably
  • Experience with Python would be favourably considered

Allianz is committed to employment equity and promoting an inclusive work environment.  We welcome applications from men and women regardless of race or cultural diversity, age, sexual orientation or identity, disability, political and religious standing as well as thinking and working styles.  We invite you to let us know of any reasonable adjustments you require to equitably participate in the recruitment process or in performing the requirements of the role.



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