Group Head of Data Science//Up to €140k + Package//Flexible working arrangement//Global retail business

Summary

My client is a leading retail convenience company operating globally. They specialise in providing fuel, food, and convenience store services with a focus on delivering exceptional customer experiences. The role will form part of the commercial leadership team and is an exciting opportunity to join the business as a Head of Data Sciences to shape and lead a strategy, team and the wider business. You will be responsible for reviewing raw data across the group and turning it into meaningful information that the company can use to improve its business processes and performance. The primary duties include analysing large data sets, creating algorithms that manage & organise information, and writing applications that translate data and identify patterns.

Key Responsibilities

• Hypothesis Generation: Analysing customer data from diverse sources to formulate hypotheses that could significantly impact business operations if validated.
• Insight Generation: Extracting valuable insights from large databases containing structured and unstructured data to identify trends and patterns in customer behavior.
• Product Lifecycle Analysis: Understanding the stages of product delivery and conducting expert analyses at each stage to contribute to decision-making and optimise product performance.
• Data Transformation and Visualisation: Utilising our data platform to transform big data into meaningful datasets and developing interactive dashboards that combine visuals with Real Time data.
• Machine Learning Pipeline Development: Building scalable machine learning pipelines and employing feature engineering and optimisation methods to enhance dataset performance.
• Data Integration and Testing: Collaborating with IT Technologists to integrate and separate data feeds, map, produce, transform, and test new scalable datasets to ensure accuracy and reliability.

Technical Skills

• Experience in data visualisation and presenting data in graph or pictorial format
• Proficiency in designing algorithms and using statistical and problem structuring methods
• Ability to clean and validate data to ensure uniformity and accuracy
• Ability to use linear and non-linear regression, logistic regression, models and classification techniques for data analysis, clustering, dimensionality reduction, k-NN and pipeline
• Proficiency in mathematical computing
• Interpersonal skills
• Excellent verbal and written communication skills