We solve real-world problems for hundreds of thousands of colleagues and millions of customers worldwide, whether they choose to shop with us in store or online. The work we do is critical to the business, and we’re looking to broaden our teams to help us to iterate, innovate and deliver more quickly.
Cambridge Spark is a leader in personalised Data Science training. We offer intensive bootcamps, graduate schemes, apprenticeships and team training solutions which are delivered by industry and academic experts, complemented by our proprietary AI-powered data science talent attraction, assessment and development platform, K.A.T.E.®.
Our team consists of field specialists and come from a range of backgrounds, including PhDs and Researchers in Machine Learning from Cambridge University, Oxford University, and UCL - as well as Developers with industry experience from leading companies including Google, Microsoft Research, Amazon, Morgan Stanley and Oracle.
QuantumBlack is an advanced analytics firm operating at the intersection of strategy, technology and design to improve performance outcomes for companies.
QuantumBlack was born and proven in Formula 1 – where teams live and breathe data. Today, we are still fascinated by how a marginal gain can have a significant impact on the performance of any organisation.
QBE Insurance Group is one of the world's leading international insurers and reinsurers, headquartered in Sydney, Australia. We operate in 37 countries with a presence in all key insurance markets, and are lead underwriters within our chosen markets, setting rates and conditions.
In Europe, QBE offers an extensive range of business insurance products from the standard suite of property, liability and motor to the specialist financial lines, marine, energy and political risk. QBE works in partnership with insurance intermediaries to deliver tailored cover to businesses from sole traders, via its online trading platform, to SMEs, large corporates and global multinationals.
We are active and heavy users of Python and the PyData stack, which we use in concert with a broad set of machine learning tools and techniques such as catastrophe simulation, natural language processing, and data visualisation. The use of data is fundamental to improve our decision making for pricing, risk selection, fraud, claims, customer acquisition and other problems.
We are on a journey to be the most progressive user of data science within commercial insurance.