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Data Scientist - Production
Job summary
A leading consumer goods company is seeking a Data Scientist to manage the deployment and maintenance of AI models in production. The candidate will collaborate with teams to integrate machine learning solutions and ensure model performance. Ideal applicants should have a Master’s degree in a relevant field and strong skills in Python and SQL. This position offers an exciting opportunity for personal growth and challenges in a diverse environment.
Qualifications
- Experience in deploying and maintaining machine learning models in production environments.
- Excellent problem-solving skills and attention to detail.
Responsibilities
- Deploy and maintain AI models in production, ensuring efficient refreshes as needed.
- Collaborate with the UDP team to integrate machine learning solutions.
- Represent CCEP in third-party projects.
Skills
Education
Job Description
Are you looking for new challenges and personal growth within Coca-Cola Europacific Partners? Then we have a great opportunity for you! 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 - Production Level: Manager: Experience: 4 years Role Overview: The Data Scientist - Production ensures the efficient transition of machine learning models from exploration to production. Working closely with the UDP team, this role is responsible for deploying, maintaining, and evolving AI models, ensuring their reliability and scalability in production environments. The role also includes representing CCEP in third-party projects to ensure smooth handovers.
- Deploy and maintain AI models in production, ensuring efficient refreshes as needed.
- Collaborate with the UDP team to integrate machine learning solutions into production workflows.
- Represent CCEP in third-party projects, ensuring smooth transitions post-handover.
- Monitor model performance and address requests for maintenance and evolution.
- Implement best practices in MLOps for scalable and reliable model deployment.
- Master’s degree in Computer Science, Data Science, or a related field.
- Experience in deploying and maintaining machine learning models in production environments.
- Proficiency in Python, SQL, and cloud platforms (e.g., Databricks, Azure).
- Strong understanding of MLOps practices, including CI/CD pipelines and model monitoring.
- Excellent problem-solving skills and attention to detail.
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.
We believe that equal opportunities means, diversity and fair treatment for all. As we have expanded recently into alcohol ready to drink Jack Daniel’s and Coca-Cola we recognise that some people prefer not to participate in alcohol related sales, interactions, or promotions. If that’s true for you – please raise this with your talent acquisition contact who will advise you on whether this role includes activities related to our alcohol portfolio.
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.
Hiring Manager: Muhammad Shakir Hussain
Recruiter: Tegan McColl
Grade: G3
Location: Pan EU : Spain:Madrid : Madrid || Pan EU : Spain:Cataluna : Barcelona || Pan EU : United Kingdom:CCEP Site Locations : Uxbridge
We are Coca-Cola Europacific Partners (CCEP) – a dedicated team of 42,000 people, serving customers in 31 countries, who work together to make, move and sell some of the world’s most loved drinks. We are a global business and one of the leading consumer goods companies in the world.
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.
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