At a Glance
- Tasks: Lead a team to develop AI systems for optimising logistics and planning.
- Company: Join Ocado Technology, a leader in innovative shopping solutions.
- Benefits: Enjoy hybrid working, 30 days leave, and wellness support.
- Other info: Diverse team culture with excellent career growth opportunities.
- Why this job: Make a real impact with cutting-edge AI in a dynamic environment.
- Qualifications: Strong data science background and leadership experience required.
The predicted salary is between 70000 - 90000 € per year.
Ocado Technology is changing the way the world shops using advanced Artificial Intelligence, Machine Learning, Robotics, Big Data, Cloud and IoT. We develop the innovative software and hardware systems that power Ocado.com, as well as the unique ‘Ocado Smart Platform’ which is being implemented by ambitious retailers across the world from Europe to America, Asia and beyond.
As a Data Science Manager in Logistics, you will lead the Autoplanner team to build AI systems that unify planning across global warehouses and last-mile assets. Your mission is to deliver a single optimised plan that maximises profit and minimises lateness, bridging the gap between advanced research and live operational impact. Collaborating with Product and Engineering teams, you will integrate data science models into our global backend services to enhance the Ocado Smart Platform. Beyond technical delivery, you will scale our operations by fostering a high-performing culture, mentoring team members, and driving best practices.
Key Responsibilities- Lead a multidisciplinary team of data scientists and software engineers to research, develop, and deploy sophisticated planning systems.
- Drive the development of machine learning solutions focused on predicting and optimising route requirements, staffing needs, and sales estimations.
- Identify new opportunities to add business value through machine learning and create proofs of concept to engage product managers.
- Collaborate with product teams to ensure the successful integration of data science models with backend services.
- Maintain a healthy delivery pace and cadence within the team, ensuring consistent output and continuous improvement.
- Provide dedicated mentorship and coaching through weekly 1:1s, goal setting, and regular feedback.
- Manage the end-to-end recruitment and development of a diverse team of technical experts.
- Champion and raise the bar for data science best practices and processes across the wider organisation.
- Manage the delivery of AI systems that balance day-to-day profit with operational excellence.
- Navigate technical and organisational ambiguity to deliver pragmatic, iterative results in a fast-paced environment.
- A strong data science background with solid Python coding skills.
- Proven experience in building and deploying end-to-end machine learning solutions from discovery to production.
- Demonstrated experience in coaching, developing, and leading high-performing technical teams.
- A collaborative mindset with evidence of working effectively across different crafts and being comfortable with peer challenge.
- A pragmatic approach to delivery, focusing on quick outputs to learn and iterate fast.
- Comfort with ambiguity and a curious nature that encourages outside the box thinking.
- Experience with operational research and optimisation techniques.
- Experience in building and deploying Java backends and React frontends in a production environment.
- Hybrid working patterns meaning part of the working week can be spent working remotely (typically 3 days per week).
- 30 days working from anywhere policy.
- Wellbeing support through Apps such as Unmind and an Employee Assistance Programme.
- 25 days annual leave, rising to 27 days after 5 years service (plus optional holiday purchase).
- Pension scheme (various options available including employer contribution matching up to 7%).
- Private Medical Insurance.
- 22 weeks paid maternity leave and 6 weeks paid paternity leave (once relevant service requirements complete).
- Train Ticket loan (interest-free).
- Cycle to Work Scheme.
- Share Options (5-10%).
- Opportunity to participate in Sharesave and Buy as You Earn share schemes.
- 15% discount on Ocado.com and free delivery for all employees.
- Income Protection (can be up to 50% of salary for 3 years).
- Life Assurance (3 x annual salary).
We are looking for individuality and we value diversity. We are an equal opportunities employer and we are committed to treating all applicants and employees fairly and equally. We are committed to making reasonable adjustments to provide a positive, barrier‑free recruitment process and supportive work environment. If you have any support or access requirements, we encourage you to advise us at the time of application.
Data Science Manager - Logistics in London employer: Ocado Technology
Ocado Technology is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of London and Hatfield. With hybrid working options, generous leave policies, and comprehensive wellbeing support, employees are empowered to thrive both personally and professionally. The company prioritises employee growth through mentorship and diverse team development, making it an ideal place for those seeking meaningful and rewarding careers in data science and logistics.
StudySmarter Expert Advice🤫
We think this is how you could land Data Science Manager - Logistics in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those related to logistics and optimisation. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by practising common data science questions and case studies. Make sure you can explain your thought process clearly, as collaboration is key in this role.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our team at Ocado Technology.
We think you need these skills to ace Data Science Manager - Logistics in London
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your strong data science background and Python coding skills in your application. We want to see how you've built and deployed machine learning solutions, so don’t hold back on the details!
Be a Team Player:We love collaboration! Share examples of how you've worked effectively across different teams and crafts. Show us your experience in coaching and leading high-performing teams – it’s a big plus for us!
Keep It Pragmatic:We appreciate a pragmatic approach to delivery. In your application, mention how you focus on quick outputs to learn and iterate fast. This mindset is key to thriving in our fast-paced environment.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and get you into our system. Plus, we can’t wait to see what you bring to the table!
How to prepare for a job interview at Ocado Technology
✨Know Your Data Science Stuff
Make sure you brush up on your data science fundamentals, especially around Python and machine learning. Be ready to discuss your past projects and how you've deployed end-to-end solutions. This will show that you not only understand the theory but can also apply it in real-world scenarios.
✨Show Off Your Leadership Skills
As a Data Science Manager, you'll need to demonstrate your ability to lead and mentor a team. Prepare examples of how you've coached team members or driven best practices in previous roles. Highlight your collaborative mindset and how you've worked effectively across different teams.
✨Be Ready for Technical Challenges
Expect some technical questions or case studies during the interview. Practice explaining complex concepts in simple terms, as you may need to bridge the gap between advanced research and operational impact. Think about how you would approach problems related to logistics and optimisation.
✨Embrace the Ambiguity
Ocado Technology thrives in a fast-paced environment with lots of moving parts. Be prepared to discuss how you've navigated ambiguity in past projects. Share examples of how you've iterated quickly and learned from your experiences, showing that you're adaptable and curious.
