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Data Scientist Manager
- Uxbridge, England, United Kingdom
- Uxbridge, England, United Kingdom
Über
Are you looking for new challenges and personal growth within Coca-Cola Europacific Partners? Then we have a great opportunity for you! Find out if this opportunity is a good fit by reading all of the information that follows below. Do you have a personality with the power to influence and connect? Can you sustain the pace to keep on growing? Will you make an impact with your desire to win?
Data Scientist Manager:
Are you passionate about using data to solve complex business challenges? We re looking for a Data Scientist Manager to join our team and play a key role in developing innovative, data-driven solutions that enhance supply chain performance. This is an exciting opportunity for an analytically minded professional with a strong foundation in statistics and experience applying advanced modelling techniques to real-world business problems.
Working closely with cross-functional stakeholders, you will leverage statistical modelling, machine learning, and predictive analytics to improve forecasting accuracy, optimise inventory, and drive operational efficiency.
Key Responsibilities:
Apply statistical modelling and machine learning techniques to address supply chain challenges, including demand forecasting, inventory optimisation, and replenishment planning.
Develop, test, validate, and deploy predictive models using robust statistical methodologies, including regression analysis, time series forecasting, and Bayesian approaches.
Partner with supply chain stakeholders, including demand planners and inventory managers, to translate business requirements into actionable analytical solutions.
Analyse large and complex datasets to uncover insights that improve service levels, reduce costs, and optimise inventory performance.
Contribute to the design and development of scalable data science solutions within cloud-based environments such as Databricks and Azure.
Present findings, insights, and recommendations clearly to both technical and non-technical audiences.
Support the ongoing development and advancement of data science capabilities across the organisation.
Requirements:Essential Qualifications:
Master s degree in Statistics, Econometrics, Mathematics, or a related quantitative discipline.
Minimum of 4 years
experience in a Data Science, Advanced Analytics, or similar role.
Strong understanding of statistical concepts, including:
Probabilistic modelling
Statistical inference
Time series analysis
Forecasting methodologies
Proficiency in Python or R for data analysis, modelling, and machine learning.
Experience applying analytics within a supply chain environment.
Strong analytical thinking and problem-solving abilities with a focus on methodological rigour.
Excellent communication and stakeholder engagement skills.
Ability to collaborate effectively within cross-functional teams.
Why Join Us? You ll have the opportunity to work on impactful projects that directly influence business performance and decision-making. Joining our team means being part of a collaborative environment where innovation, continuous learning, and data-driven thinking are valued and encouraged.
If you're excited about transforming complex data into meaningful business outcomes and want to make a tangible impact within supply chain operations, we'd love to hear from you.
Application
If this role is of interest to you please upload a recent copy of your CV and a member of the Talent Acquisition team will be in touch. xlzlddp
We believe that equal opportunities means inclusion, diversity and fair treatment for all.
We aim to make our recruitment process as comfortable and accessible as possible and would appreciate it if you would advise us of any particular requirements, adjustments or requests you may have to help us ensure that your experience is enjoyable.
Job Information:
Hiring Manager: Muhammad Shakir Hussain
Recruiter: Tegan McColl
Grade:
Location: United Kingdom : CCEP Site Locations : Uxbridge
Spain : Madrid : Madrid
Sprachkenntnisse
- English
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