Data Scientist/Statistician

  • Zurich Insurance
  • Fareham, UK
  • UK
  • 1 week remaining

In the role of Data scientist/ Statistician you will be part of a growing and exciting Predictive Analytics Team with UK Underwriting, which is responsible for delivering predictive modelling, statistical services and solutions across the business.
Your job will comprise claim cost modelling, geographical modelling, demand modelling, as well as providing Research and Development services to test and implement new data sources and statistical techniques that can drive and improve our performance.
You will have the opportunity to make an immediate impact on business success and by using predictive modelling, bring the right solutions to the whole organisation.

Key Responsibilities:

  • Support the analytical development of UK Underwriting teams through data gathering, analysis and modelling under the direction of a more senior statistician.
  • Demonstrate increasing knowledge of statistical techniques and procedures, including trend analysis, profiling and predictive modelling, to be able to provide first class service to external and internal customers.
  • Provide regular insight and analysis, using multiple data sources.
  • Work closely with the data team to steer the development of the analytical capability
  • Support project teams.
  • Contribute to a positive and supportive team culture.

Your skills and experience:

  • Statistician/ data scientist with some experience in predictive analytics
  • Strong degree or MSc/PhD in a numerical subject (Maths, Statistics, Science)
  • Some experience applying machine learning models and predictive analytical techniques
  • Experienced in advanced statistical analysis and data manipulation techniques
  • Knowledge of at least one of the following machine learning and data manipulation packages (R, Python)
  • Previous experience of the insurance/financial industry is desirable but not essential

Who we are

Zurich is one of the world’s leading insurance groups, and one of the few to operate on a global basis. Our mission is to help our customers understand and protect themselves from risk. With about 55,000 employees serving customers in more than 170 countries, we aspire to become the best global insurer as measured by our shareholders, customers and employees. We help individuals, small and medium sized companies and global corporations around the world understand and protect themselves from risk by offering a wide range of insurance products, solutions and advisory services. Being an international insurer with such a wide range of products means Zurich is an ideal company to work for post university as you can gain exposure to multiple areas of the company and multiple working cultures across the world. For example, Zurich best actuaries are given the opportunity to apply for their International Actuarial Rotation program after two years, which gives actuaries the opportunity to work abroad for two years.

The reward:

In return we are offering an attractive salary plus a generous benefits package including bonus and defined contribution pension scheme. We are committed to continuous improvement and we offer access to a comprehensive range of training and development opportunities

Further information:

At Zurich, we aim to have a diverse mix of employees that reflects our customers and the communities in which we live and work. Our diversity and inclusion initiatives are shaping an environment where everyone feels welcome, regardless of age, gender, religion, ability, culture, sexual orientation or mental health status. Our approach ensures that Zurich is a place that values different opinions, respects personal needs, and provides equal opportunities for all. We’re also happy to consider flexible working arrangements and welcome applications from everyone.

So make a difference. Be challenged. Be inspired. Be supported, Love what you do. Work for us.

To apply for this job please visit the following URL: https://zurich.taleo.net/careersection/zurich_ext_uk_en/jobdetail.ftl →


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