Senior Data Scientist


Castle Park, Cambridge, UK

Ref: 959504


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Amazon’s Cambridge UK based Inventory Prediction and Bridging (IPB) team is looking for an experienced, passionate and hard-working Senior Data Scientist to join our fast paced stimulating environment, to help invent the future of retail with technology, and to turn big data into actionable insights.

The IPB team is part of the Supply Chain Optimization Technology (SCOT) team, within the Operations Organization. The charter of the SCOT team is to maximize Amazon’s return on our inventory investment in terms of Free Cash Flow, and customer satisfaction. We accomplish this by applying advanced statistical methods and empirical analysis to predict and evaluate Amazon’s inventory needs. We provide data-driven recommendations to senior business leaders to optimize this critical element of Amazon’s supply chain. All this puts the Inventory Planning group at the nexus of operations, logistics, capacity planning, and our retail business teams.

As a Sr. Data Scientist on the IPB team, you will analyze large amounts of business data and develop metrics and business cases that will continually delight our customers worldwide. You will work with a team of software engineers, business intelligence engineers and product managers, to build accurate predictive models and algorithms, and deploy automated software solutions to make data more actionable to manage our business at scale.

Successful outstanding candidates will bring strong technical and analytical abilities, combined with a passion for delivering results for customers, internal and external. This role requires a high degree of ownership, and a drive, to solve some of the most challenging data and analytic problems in retail.


  • Directly contribute to the design and development of prediction systems.
  • Utilizing code (Python, R, Scala, etc.) for analyzing data and building statistical models to solve specific business problems.
  • Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters.
  • Apply statistical or machine learning knowledge to specific business problems and data.
  • Collaborate with colleagues from multidisciplinary science, engineering and business backgrounds.
  • Conduct written and verbal presentations to share insights and recommendations to audiences of varying levels of technical sophistication. is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation


  • Master’s degree in a quantitative field such as Statistics, Applied Mathematics, Physics, Engineering, Computer Science, or Economics.
  • 5+ years' of industry experience with data querying languages (e.g. SQL), scripting languages (e.g. Python, R), or statistical/mathematical software (e.g. R, SAS, Matlab, etc.).
  • At least 3 years’ experience articulating business questions and using quantitative modeling and statistical analysis techniques to arrive at a solution using available data.


  • Depth and breadth in quantitative knowledge. Excellent quantitative modeling, statistical analysis skills and problem-solving skills.
  • Demonstrable record of accomplishment of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment.
  • Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations.
  • Experience with modeling sequential data, statistical forecasting, and time series models.
  • Experience processing, filtering, and presenting large quantities (millions to billions of rows) of data.
  • Depth of knowledge in machine learning algorithms.
  • Understanding of Amazon Web Services (AWS) technologies.
  • Experience in supply chain is a plus.


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