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- Tasks: Deploy and maintain AI models, ensuring their efficiency and reliability in production.
- Company: Join Coca-Cola Europacific Partners, a global leader in consumer goods with 42,000 passionate team members.
- Benefits: Enjoy a dynamic work environment with opportunities for personal growth and diverse projects.
- Why this job: Make an impact by integrating cutting-edge AI solutions and collaborating on exciting third-party projects.
- Qualifications: Master's degree in Data Science or related field; experience in machine learning model deployment required.
- Other info: Flexible recruitment process to accommodate your needs; discuss any preferences with the talent acquisition team.
The predicted salary is between 43200 - 72000 £ per year.
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?
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.
Key Responsibilities:
- 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.
Qualifications:
- 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 inclusion, 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.
Job Information:
- Hiring Manager: Muhammad Shakir Hussain
- Recruiter: Robin Meyer
- 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.
Data Scientist - Production employer: Coca-Cola Europacific Partners
Contact Detail:
Coca-Cola Europacific Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Production
✨Tip Number 1
Familiarise yourself with Coca-Cola Europacific Partners' values and culture. Understanding their mission and how they operate can help you align your responses during interviews, showcasing that you're not just a fit for the role but also for the company.
✨Tip Number 2
Network with current or former employees of CCEP, especially those in data science roles. They can provide insights into the company’s expectations and the nuances of the team dynamics, which can be invaluable during your interview.
✨Tip Number 3
Prepare to discuss specific examples of your experience with deploying machine learning models. Be ready to explain your approach to MLOps practices, as this will demonstrate your technical expertise and problem-solving skills relevant to the role.
✨Tip Number 4
Stay updated on the latest trends in AI and machine learning, particularly in production environments. Being able to discuss recent advancements or case studies can set you apart and show your passion for the field.
We think you need these skills to ace Data Scientist - Production
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in deploying and maintaining machine learning models. Emphasise your proficiency in Python, SQL, and any cloud platforms you've worked with, as these are key requirements for the role.
Craft a Strong Cover Letter: Write a cover letter that showcases your passion for data science and your ability to influence and connect with teams. Mention specific projects where you've successfully implemented MLOps practices or collaborated on third-party projects.
Highlight Problem-Solving Skills: In your application, provide examples of how you've tackled complex problems in previous roles. This could include challenges faced during model deployment or maintenance, and how you ensured reliability and scalability.
Review and Edit: Before submitting your application, take the time to review and edit your documents. Check for clarity, grammar, and spelling errors. A polished application reflects your attention to detail, which is crucial for a Data Scientist role.
How to prepare for a job interview at Coca-Cola Europacific Partners
✨Showcase Your Technical Skills
Make sure to highlight your experience with deploying and maintaining machine learning models. Be prepared to discuss specific projects where you've used Python, SQL, or cloud platforms like Databricks or Azure.
✨Understand MLOps Practices
Familiarise yourself with MLOps best practices, especially CI/CD pipelines and model monitoring. Be ready to explain how you have implemented these in past roles to ensure scalable and reliable model deployment.
✨Demonstrate Collaboration Skills
Since the role involves working closely with the UDP team, be prepared to discuss your experience in collaborative environments. Share examples of how you've successfully integrated machine learning solutions into production workflows.
✨Prepare for Problem-Solving Questions
Expect questions that assess your problem-solving abilities. Think of scenarios where you've had to address model performance issues or maintenance requests, and be ready to walk through your thought process.
