Zurich Gruppe Deutschland

Data Scientist - Life and Investments

Job description

The Opportunity

Are you interested in a new challenge to reimagine the future of insurance through the use of Data? Do you want to be part of this exciting journey as we build solutions and experiences from the ground up? Zurich globally has a bold purpose to create a brighter future for our customers, and in doing this, transform the industry and expand our horizons.

Zurich Life Australia is undergoing an exciting transformation and Data in one of our key strategic enablers! We are creating new teams, capabilities, enhancing and uplifting our ability to support our transformation and growth aspirations. As a result, we are looking for a dynamic and driven Data Scientist to join this exciting and bold journey and be part of the transformation to be an insights driven organisation.

About the role

Zurich Life’s Data & Analytics team is accountable for the full end to end Data delivery lifecycle, from Data Management through to automating processes, implementing Data products and solutions, providing Data insights, and solving business and customer problems via the use of analytics, machine learning and AI driven solutions.

As a Data Scientist, you will liaise with critical internal & external stakeholders to provide insights, recommendations, and solutions to complex data problems, which will inform the platform’s scope of change for new sources, models, and enrichments.

You will take ownership and be able to drive solutions with stakeholders to ensure each data product delivers intended business value and be expected to look for continuous improvement and innovation in processes and insights driven by business need and advancements in data science and technology.

Important to your success

To be successful in the role, you will have 5+ years of functional experience working with data in a similar analytical role, ideally with a focus on supporting a financial services business (Insurance industry experience would be a bonus).

In addition, you will have:

  • Tertiary qualifications in Data Science, Computer Science, Information Technology, Big Data or Machine Learning.
  • Experience working with Big Data to provide Diagnostic, Predictive Analytics.
  • Experience in statistical and econometric modelling, performing quantitative analysis, and technological data mining and analysis techniques.
  • Experience working with Python, R or SAS.
  • Proficiency with SQL, MySQL, SQLite, Oracle, RDBMS, IBM Db2.
  • Experience in building, maintaining reports and data visualisations (Alteryx, BI tools with Power BI and using Informatica tools).
  • Experience working with Data via On premise and public cloud infrastructure environment.

Finally, you will have the ability to work individually and as part of the team by leading and providing support and guidance to fellow team members and have a proven ability to build and manage relationships with stakeholders at all levels.

Zurich is here to support you

As you make a difference and have real impact on business outcomes, you’ll feel the support of being part of a strong and stable company. As a long-standing player in the insurance industry, we make every effort to address the career development needs and plans of our employees to ensure their success in the future. In return for your commitment and hard work Zurich can offer you competitive remuneration, an excellent bonus structure, an annual lifestyle payment and employee discounts. In addition, Zurich is proud of its corporate and social responsibility and offers every employee an annual volunteer day.

So, make a difference. Be challenged. Be inspired. Be supported. Love what you do. Work with us. Apply today!

Zurich is committed to ensuring that our process is fair and accessible for all candidates. If you require any special accommodations to participate in our recruitment process, please reach out to us on human.resources@zurich.com.au Please note, we will not accept applications sent to this email address, please apply via our careers page.

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