Job Purpose
At Halfords we recognise our most important asset, after our people, is data, which is why we have invested in an Azure Databricks data lake. The challenge of course is to have skilled resource to unlock the valuable business insight within the data.
The Group Supply Chain Data Scientist is a new role and will work alongside the Group Supply Chain Analytics Manager. Both roles are responsible for analysing and interpreting large amounts of data from a range of internal and external sources, using algorithmic, data mining, artificial intelligence, machine learning and statistical tools, to make it available to Merchandise Planners and wider Supply Chain teams for decision making.
The Group Supply Chain Data Scientist will be responsible for the creation and maintenance of weekly KPI dashboards and actionable insight and use statistical and analytical methods plus AI tools to automate specific processes within Supply Chain and develop smart solutions to business challenges.
The role aims to ensure Halfords can leverage competitive advantage through the deployment of best-in-class analytics across planning and the end-to-end supply chain, driving continuous efficiency and effectiveness through automation and informed decision making, linking business strategy to insight.
Key Responsibilities
Work closely with the Supply Chain stakeholders to understand business goals and determine how data can be used to achieve these goals. Synthesize information from multiple internal and external sources to solve problems critical to the Supply Chain. Influence the ingestion of new data sources into the Group Data Platform, support the testing of new data and creation of Supply Chain measures for the business to use. Use machine learning tools and statistical techniques to produce solutions to problems and enable managers to make proactive decisions. Create clear dashboards and reports that provide compelling insight about our Group Supply Chain performance and highlight opportunities for improved customer service and business efficiencies. Interpret analytical results and clearly communicate findings, translating technical data insights into actionable strategies for non-technical stakeholders. Facilitate embedding a self-service capability for operational business users including automating as far as possible to reduce manual intervention and drive efficiency. Stay up to date with the latest Data Science technology, techniques and methods.
Key Skills/Experience
Proven experience as a Data Scientist or Data Analyst. Experience in data mining and data wrangling. Experience in open source big-data technologies and cloud (. Microsoft Azure). Experience of data warehouse and data lake structures . Azure Databricks, Snowflake as well as data visualisation tools . Microsoft Power BI, Tableau. Knowledge of statistical programming and database query languages . SQL, Python (including PySpark, a Python API for Spark, useful for Azure Databricks). R and Scala are an asset. Strong applied statistical and probability skills, including knowledge of statistical tests, distributions and regression. Understanding of machine-learning methods, like k-nearest neighbours, naive Bayes classifiers, support vector machines, random forests and an understanding of Operations Research. Strong problem-solving aptitude. Knowledge of retail Supply Chain and Merchandise Planning processes is an asset. Excellent communication and presentation skills demonstrating the ability to describe findings to a technical and non-technical audience. BSc/BA in computer science, mathematics, statistics, MORSE or relevant field; graduate degree in data science or another quantitative field is essential.
Personal characteristics
Analytical mind and business acumen. Highly numerate and high data handling capability. Ability to work accurately at pace. Attention to detail. Proactive, ‘can-do’ attitude with a solution-oriented approach. A continuous improvement mind-set. Constantly looking for ways to better things. Team player, with a collaborative style. Sense of humour. Personifies the Halfords values of ‘pride in expertise’, ‘wow our customers’, ‘be better every day’ and ‘one Halfords family’.
