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Senior Data Scientist at Marks & Spencer

Job purpose 

Work alongside like-minded Data Scientists and Analysts to apply best practice statistical and analytical techniques to business issues

Key accountabilities and measures

• Use expert knowledge of data science techniques and statistics to regularly deliver complex projects with a robust commercial approach

• Build and maintain the algorithms required to drive value from Loyalty in M&S

• Regular drumbeat of delivery of data science projects – both large and small – that drives business benefit and gives M&S a competitive advantage

• Deliver high quality actionable data science by performing ad hoc analysis to predict, measure and interpret business trends. • Demonstrate a culture of analytical ‘curiosity’ through innovative, data driven insights on business questions

• Work alongside Lead Data Scientist to develop the data science agenda within the CIU

• Implement a highly visual and commercial approach when delivering data science projects that engages and challenges the thinking of non / less technical audiences. Clearly and concisely communicate data science insight that then gets buy in

• Similarly work alongside the rest of the CIU Analytics team to champion/implement self-service and data-driven decisioning for the CIU client base with a strong emphasis on automation to lift the team out of BAU

• Act as consultant to CIU analysts and other M&S functions, such as Marketing, Merchandising or Logistics to identify opportunities and appropriate solutions to problems

• Work as part of a team to scan and maintain a presence within the market for opportunities in optimisation, analytical techniques, visualisation, tools and big data working with M&S Big data / IT Teams to prioritise and scope improvements

• Engage the CIU analytical community by pushing best practice, helping coach data scientists and upskilling business analysts

Key skills

• PhD or MSc. in a numerate subject is preferred e.g. Machine Learning, Computer Science, Statistics

• Experience in developing and deploying machine learning algorithms using Python or R.

• Proficient with SQL and NoSQL data bases

• Prior experience of using Apache Spark to develop and deploy data science projects.

• Comprehensive proficiency in key programming languages (e.g. Python, Java, R, SPARK, SQL, etc) and software development skills.

• Expert in mining large & complex data sets - both structured and unstructured data and including (but not limited to) efficient extraction of data, transformation and application

• Considerable experience working as a data scientist.

Key relationships and stakeholders

• CIU and Loyalty wider team 

• Internal clients from the business, especially various Leadership teams

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by Tsutomu Narushima