Time Type: Full time
Worker Type: Employee
Data Scientist in the CUO Pricing and Data Science team
QBE Insurance Group is one of the world's top 20 general insurance and reinsurance companies, with operations in all the key insurance markets. QBE is listed on the Australian Securities Exchange and is headquartered in Sydney. We employ more than 14,000 people in 43 countries.
Our underlying business strategy is to maintain operations in the key global insurance markets and, where possible, to be a lead underwriter for selected lines of business.
Who’ll you’ll be working with:
QBE Europe specialise in commercial insurance providing cover for a wide variety of risks in multiple industries such as Energy, Cyber, Property, Marine, Casualty, Motor, and Financial Lines.
Our Data Scientists utilise machine learning and artificial intelligence technologies to help QBE select and price risk, detect fraudulent claims, identify target opportunities, develop new products, and make operational processes more efficient.
The European Operations ‘Pricing and Data Science’ team consists of 12 experienced data scientists and 15 pricing actuaries. Additionally, we collaborate with the internal application development team who provide Software Engineering, Data Engineering, and DevOps support.
- Work in an experienced team of Data Scientists alongside experts in insurance Underwriting, Pricing, Claims, and IT
- Exposure to the London Market (international market for the world’s largest and most complex insurance risks), UK Insurance, European Insurance, and Reinsurance sectors
- Utilise high quality Data Science lab environments in QBE’s Google Cloud Platform
- Competitive compensation, pension and benefits
- Flexible working
- Modern headquarters on Fenchurch Street with dual monitors and standing desks
- Strong executive support and sponsorship
Your responsibilities for this role may include, but are not limited to:
- Work in close partnership with the Underwriting and Pricing teams to add value to the business using Data Science techniques and modern technologies
- Implementation of end-to-end Data Science workflows: discovery and problem definition, data acquisition and processing, model build and tuning, performance validation, and results communication
- Development of high-quality, sustainable, and compliant Data Products and Services
- Conduct geospatial analysis and modelling using large-scale telematics data
- Collaborate with the IT Applications Engineering team to deploy and maintain Data Products and Services
- Develop and maintain strong technical Data Science skills, collaborate with the team through code review, learn from others and share knowledge within the team
You will need to be able to display you have the following qualifications, experience, and skills:
- Degree in Science, Technology, Engineering, Mathematics (STEM) subject, or equivalent expertise
- Strong skills in Python Programming and utilisation of the “scientific programming stack”
- Knowledge of SQL
- Skills in geospatial data analysis and tools
- Demonstrable knowledge, ability, and experience of implementing data science or machine learning workflows
- Ability to communicate methods and insights verbally and in writing, and convey intuition behind complex subjects, to expert and non-expert audiences
- An understanding of data visualisation principles
- An active interest and enthusiasm in understanding risk
- Proactive in identifying, dealing with problems, and actioning opportunities
- Ability to prioritise and manage workloads effectively
- Ability to find common ground, and mutually beneficial outcomes when dealing with stakeholders
- Desire to continuously learn about cloud-based Data Science technologies and develop skills on processing and usage of large datasets
- Commercial understanding of Risk and Risk Transfer (any domain / industry)
- Expertise in Data Engineering, Software Engineering, or Machine Learning on Google Cloud or equivalent platform
- Understanding of Generalised Linear Models, Gradient Boosted Regression, Deep Learning
- Knowledge of data protection, privacy, ethics, and masking
- Actuarial Pricing knowledge
- Experience with Unix operating systems
The interview process is three stage: a first-round call, a ’take-away’ technical modelling challenge to be evaluated by Senior Data Scientists, and a third round general and technical interview
At QBE, we view our people as our most precious asset. We understand the importance of fostering a work environment that is responsive to the changing needs of today's workforce. QBE aims to build a workplace that is fair and inclusive because we want to attract and retain the best people to do the job. We’re ‘Happy to talk Flexible Working’.
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How to Apply:
To submit your application, click Apply and follow the step by step process.
Equal Employment Opportunity:
QBE is an equal opportunity employer and is required to comply with equal employment opportunity legislation in each jurisdiction it operates.