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- Tasks: Lead a data science team to optimise logistics and deploy machine learning models.
- Company: A leading tech company in Greater London with a focus on innovation.
- Benefits: Hybrid work, private medical insurance, and extensive professional development opportunities.
- Why this job: Make a real impact in logistics while leading a talented team in a dynamic environment.
- Qualifications: Experience in data science, machine learning, and stakeholder management.
- Other info: Great opportunity for career growth and team leadership.
The predicted salary is between 80000 - 100000 £ per year.
A leading technology company in Greater London is seeking a Director of Data to lead a high-impact data science cluster. This role focuses on logistics optimization and the deployment of machine learning models in production.
The ideal candidate will promote collaboration between data science and engineering while managing complex stakeholder relationships.
The position offers a hybrid working pattern, extensive benefits including private medical insurance, and significant opportunities for professional development and team leadership.
Head of Data & ML for Logistics & Fulfilment (Hybrid) employer: Ocado Technology Group
Contact Detail:
Ocado Technology Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Head of Data & ML for Logistics & Fulfilment (Hybrid)
✨Tip Number 1
Network like a pro! Reach out to people in the logistics and data science fields on LinkedIn. Join relevant groups and engage in discussions to get your name out there and show off your expertise.
✨Tip Number 2
Prepare for those interviews! Research common questions for leadership roles in data and machine learning. Practice your responses, focusing on how you've driven collaboration and managed stakeholders in past projects.
✨Tip Number 3
Showcase your projects! Create a portfolio that highlights your experience with logistics optimisation and machine learning models. This will give potential employers a clear view of what you can bring to the table.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for you, and applying directly can sometimes give you an edge over other candidates. Plus, it’s super easy!
We think you need these skills to ace Head of Data & ML for Logistics & Fulfilment (Hybrid)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Head of Data & ML role. Highlight your expertise in logistics optimisation and machine learning, as well as any leadership experience you have.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're the perfect fit for this position. Share specific examples of how you've successfully led data science projects and collaborated with engineering teams in the past.
Showcase Your Stakeholder Management Skills: In your application, emphasise your ability to manage complex stakeholder relationships. We want to see how you've navigated challenges and built strong partnerships in previous roles.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at Ocado Technology Group
✨Know Your Data Inside Out
Make sure you’re well-versed in the latest trends and technologies in data science and machine learning, especially as they relate to logistics. Brush up on your knowledge of optimisation techniques and be ready to discuss how you've applied them in past roles.
✨Showcase Your Leadership Skills
As a Head of Data, you'll need to demonstrate your ability to lead teams and manage complex stakeholder relationships. Prepare examples of how you've successfully led projects or teams in the past, focusing on collaboration between data science and engineering.
✨Prepare for Technical Questions
Expect to face technical questions that assess your understanding of machine learning models and their deployment in production. Be ready to explain your approach to solving real-world problems using data, and consider bringing along a portfolio of your work to showcase your expertise.
✨Understand the Company’s Vision
Research the company’s goals and how they align with your experience. Be prepared to discuss how you can contribute to their logistics optimisation efforts and enhance their data science cluster. Showing that you understand their mission will set you apart from other candidates.