Data Scientist_Tesco_Bangalore

 Data Scientist Job Description
At Tesco, our Data Science team focuses on modelling complex business problems and deploying data products at scale. Our work spans across multiple areas including physical stores, online, supply chain, marketing and Clubcard, where we encourage rotation amongst our Data Scientists so they can gain expertise in different subjects.
We work on several domains and problem types: online, pricing, security, fulfilment, distribution, property, IoT and computer vision are just some. Our team members spend 10% of their week on learning and personal development. Multiple academic collaborations enrich the team expertise; knowledge sharing events are regular. Furthermore, we have got a great work-life balance, team days and relaxed but engaging culture.
ROLE DESCRIPTION
This is a hands-on position where you will need to leverage your analytical mindset to find solutions to complex problems. As a Data Scientist, you will need to understand difficult business problems and prototype solutions with minimal support. Apply, modify and design algorithms and mathematical models to solve business problems on top of big data architectures (Hadoop, Spark) is a core component of the role. Our data scientists will need to be able to validate, document and present the modeling process and performances, as well as communicate complex solutions in a clear, understandable way to non-experts. Data Scientists are also responsible for promoting data science across Tesco and promote Tesco across the external Data Science community.
CANDIDATE DESCRIPTION
We are looking for ambitious individuals with a mix of statistics, programming and machine learning skills. The role requires that you have an extensive background in machine learning and data mining. A track record in modifying and designing advanced algorithms and applying them to large data sets is essential.
An ideal candidate will have a scientific mentality with the ability to ask the right questions, as well as answer them. A strong numerical higher degree in a mathematical, scientific, engineering or computer science discipline is preferable, as well as a solid understanding of mathematics and statistical principles.
Experience in one or more of the following fields is required: predictive modelling, operational research, deep learning and time series modelling. Finally, strong programming experience (Python is preferred).