Job description

Job Title: Senior Analyst/Data Scientist
Location: London
Department: Product and Commercial

Job Purpose

XLN is seeking a senior analyst with data science experience to join our Product & Commercial Analytics Team. The analytics team at XLN is the central source of data and analytics across the business ensuring that decisions are data driven. We are now looking to bring in a senior analyst to further develop the use of statistics within the business as well as develop predictive modelling, segmentation and A/B testing.

You will be an experienced analyst or data scientist who enjoys digging into data and understanding how things interact and what drives different actions. Not content with building models, you will want to understand what the drivers are and what they mean for the business. You will have worked on predictive models in a commercial environment and be looking to take the next step in your career in an environment where there are plenty of opportunities to make a difference and progress.


  • Be a subject matter expert in traditional statistical methods and predictive modelling
  • Identify opportunities where problems could be resolved using advanced analytics
  • Support the analytics team in monitoring changes in performance throughout the business and understanding the root causes
  • Provide support on data intensive projects and analysis
  • End-to-end responsibility for building propensity models
  • Develop an understanding of the drivers in the models you build and work with the team to understand what they mean
  • Propose and implement methods for testing the effectiveness of changes in the business
  • Present and communicate your findings to stakeholders across the business


  • Proficient using SQL
  • Strong programming skills in Python or R
  • Experience building propensity models in a commercial setting
  • Knowledge of common data science techniques including data preparation, exploration and visualisation
  • Knowledge of Power BI or similar BI software beneficial
  • Good analytical and problem-solving skills
  • Understanding of various data mining and statistical techniques
  • Comfortable building models from scratch
  • Strong MS Office skills including Excel, Word, PowerPoint and Outlook


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