DATA SCIENCE ANALYST- REVENUE GROWTH MANAGEMENT - MATERNITY COVER (UNTIL END 2025)

At Costa Coffee, we are what we craft. We’re reimagining coffee experiences in over 50 countries and counting, as a key part of the Coca-Cola System. Whether you get your coffee in a store, from a machine, at home, or on the go – we’ve got you covered.
We are on the lookout for an experienced Data Science Analyst with demonstrable experience of Data Science and Machine Learning to harness the potential of our brand new cutting-edge pricing tool, empowering our Global markets with insightful analysis. We are seeking a unique combination of technical competence using data analysis tools and programming languages with a natural flair for providing data and insight for decision making. You will infuse magic and creativity to support the business in driving forward decisions around pricing and promotions.
Our teams make a difference. Whether that’s working on new tech for the perfect pour, helping our teams grow, creating award-winning campaigns, crunching the numbers, or developing the latest exciting menu item; together, we stir up success.
We may be a global brand, but we haven’t forgotten our roots. That’s where the Costa Foundation and our fantastic community agenda come in. Whatever your role, you can help us change lives in coffee growing communities, and help your local community too.
We also want to help you grow in your career through amazing experiences, our apprenticeship scheme, and development programmes. At Costa, you can go beyond the day-to-day.
And as a Data Science Analyst, there’s never been a better time to join.

Being a Data Science Analyst is about so much more than bringing our coffee to the world. It’s your chance to stir up real success - which means you’ll be:

• Responsible for collecting, cleaning, modelling, analyzing and reporting data from various sources, as well as creating data visualizations and dashboards to communicate your findings. Additionally you will be
• Performing exploratory and descriptive data analysis to identify patterns, trends, outliers, and anomalies
• Applying statistical and machine learning techniques to build predictive and prescriptive models and test hypotheses
• Use feature engineering to create new data points that leverage the data to the best of our ability
• Communicating data findings and insights to internal and external stakeholders using clear and concise language and storytelling