Data Scientist, Market Analysis & Digital Pricing


Your Challenge


Are you passionate about complex analytical challenges in a commercial environment? If you have a passion in statistical modelling, data science and are comfortable working with big data, we’d like to hear from you.


We’re looking for a Data Scientist to join our team, to provide robust analysis and comprehensive predictive models in achieving data-driven commercial gain. You’ll work with a team of strong data scientists, data engineer and visualisation developer to facilitate end-to-end delivery of insights, models and data products. Your primary focus is to utilise your skills in statistical analysis and modelling to conduct AB test on prices of our digital contents, assist on experimenting key online commercial levers to optimise sales, review and improve our predictive models covering price elasticity, sales forecasting, and market share extrapolations. You will also provide a wide range of in-depth analysis to inform commercial strategies of our publishing contents. Your analysis will be communicated clearly and effectively to the business to influence decisions that maximises impact. You will build and share best practices from your analysis across both our UK and international divisions. Your remit covers both the UK and International markets, across both print and digital contents.


You are required to interrogate large databases of information utilising your high numerical literacy, strong data query skills, and your ability to partner with our data warehouse team and data engineer, to manage and manipulate large databases in a big data environment. You need great attention to detail to ensure data and analysis accuracy. This role has a strong emphasis on building and driving cutting-edge analytics that could influence our stakeholders to make the right data driven decisions in their marketing and commercial strategies.


Your Profile


We’re looking for someone who’s:


  • Passionate about reaching data-driven and quantitative conclusions, data management and visual analytics
  • Hands-on in dealing with big data using SQL, Python and R
  • 3-6 years professional experience working in business analytics or any comparable analytics positions
  • Professional experience in using R/Python as the primary tool for statistical modelling, in-depth analysis, including regression, segmentation, key univariate and multivariate analysis principles, additionally web scraping and productionise data process and mathematical models
  • Professional experience in conducting robust AB test with business recommendations that optimises KPIs
  • Confident in presenting your findings to both a technical and a non-technical audience using effective data visualisation techniques and ability to command business narratives in layman terms
  • Able to prioritise and multitask, often in deadline driven environment
  • Team player, and able to work with others across various levels and roles
  • Have a strong background in any of Maths, Statistics, Economics, Physics, Operational Research and Decision Sciences etc
  • Passionate about a career in the publishing/media industry


We love what we do so a passion for books and reading would also be a distinct advantage!


About Us

It’s an exciting time for publishing; our business is evolving and we are getting closer to our consumers than we have ever been able to before. We strive to deliver the best quality content to them that we can – ensuring they receive it how and when they want – and to make it as engaging as possible for them.

With the proliferation of data and the fast-changing dynamics within the publishing industry, quantitative analysis is more vital to our business than ever.


If this sounds like the right role for you, please apply with your CV and cover letter by the closing date, Tuesday 28th February 2020. 









Company: The Random House Group Limited 

Country: United Kingdom 

State/Region: London 

City: London 

Postal Code: SW1V 2SA 

Job ID: 41184

Job Segment: Database, Scientific, Pricing, Warehouse, Scientist, Technology, Engineering, Operations, Manufacturing, Science