Our client has just launched a new brand that is set to compete on a completely different level to where they could previously. The new brand is set to tackle a new market that the parent company has so far stayed away from.
While the established company is adjusting to the new word of data, the new brand created has been born into it. As a result, from the off, it can put data at its heart to drive decisions, gain insight and build products with customers as the priority. A world of possibility has opened up and we are looking for a Data Scientist to exploit this opportunity.
You would be working on a brand-new InsurTech product to be launched within the new brand. It will use machine learning techniques to push the boundaries of what’s possible. I can’t go into vast detail on the product itself as we are under NDA but I’m more than happy to discuss the details over the phone (about the product and new brand launch). What I can say is this product will draw on underwriting and pricing models so exposure/experience in this area is certainly beneficial (but not essential, defiantly not essential).
This is the time I talk about the ML techniques they are using but, in all honesty, it doesn’t really matter in this instance. If you have experience in one, they will use that. If you’re experienced in another, they will use that instead. They just want someone who has used ML in some way (and got some commercial benefit out of it). If you’ve got the capacity to learn one, you can learn others.
The one tech skill I’m really looking for is Python coding. Not to a data/software engineering level but strong enough for algorithm building and deployment. All the other tech can either be taught on the job, but Python is key. “If they haven’t got it we can teach it…but we need Python.”
You will be joining a small, highly performant, exceptionally bright and delivery focused team – made up of Software/Data Engineers, Architects, Data Scientists etc. You will also be working closely with a couple of 3rd party vendors/consultancies.
- Educated to at least degree level (or equivalent) in mathematics, stats, OR, data science – likely with MSc
- Knowledge and understanding of statistical and predictive modelling approaches, ideally with experience of applying them in a business context
So in summary, Data Scientist who has used ML techniques, decent Python…oh and enthusiastic, really enthusiastic.