Principal Data Scientist

Employer
Wyatt Partners
Location
Cranford, UK
Salary
Competitive
Closing date
14 Oct 2020
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Wyatt Partners are engaged to find a Principal Data Scientist for one of the most recognisable brands on the planet.

This an opportunity to have a tangible impact on the company, and also make your mark in the way the company approaches data science from a standards and infrastructure perspective.

It's a role of paradoxes to some extent in that for such a recognised global brand, there is a complete blank canvas when it comes to utilising data science for business solutions - therefore we are looking for an individual that would thrive in that 'greenfield' environment, charting their own course, with great potential to build a team around them over the next few years.

The data & its quality you will find at the company is excellent. Over 10 million rich, clean and verified customer data records being a highlight as well as numerous other internal & external data sets.

To illustrate the impact this role can have it is only 3 steps away in leadership hierachy from the CEO, which is rare for what is initially and individual contributor role.

Must have experience:
  • Fluency with Python
  • Track record of building models & providing solutions to complex business problems within a customer focused business - ideally as an employee rather than external consultant
  • Forecast Modelling
  • Experience working on projects around pricing, promotions, customer segmentation's


Nice to have experience:

  • Supply chain analytics & forecasting, logistical analysis
  • Natural Language Processing


This isn't a role for someone who wants to be part of a large team of Data Scientists, or who is looking for lots of direction in terms of the work they are undertaking.

The Successful candidate will be someone who wants to make Data Science their baby within this very well known organisation. If successful, the company can offer a leadership role in return as the division grows, and also a very real chance to add multi- millions to the company's bottom line in a short space of time, given the quality of data at your disposal
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