At a Glance
- Tasks: Lead a team to develop AI systems for optimising logistics and planning.
- Company: Join Ocado Technology, a leader in AI and machine learning innovation.
- Benefits: Enjoy hybrid working, 30 days remote work, and comprehensive wellbeing support.
- Other info: Embrace a culture of collaboration and continuous improvement in a fast-paced environment.
- Why this job: Make a real impact in logistics with cutting-edge technology and a diverse team.
- Qualifications: Strong data science background and proven leadership in technical teams.
The predicted salary is between 80000 - 100000 € 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 Lead 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 Lead - Logistics in London employer: Ocado Technology
Ocado Technology is an exceptional employer, offering a dynamic work environment where innovation meets collaboration. With hybrid working options and a strong focus on employee wellbeing, including generous leave policies and comprehensive support programmes, we empower our team members to thrive both personally and professionally. As a Data Science Lead in Logistics, you will not only lead cutting-edge projects but also have the opportunity to mentor and develop a diverse team, ensuring your growth alongside the company's ambitious goals.
StudySmarter Expert Advice🤫
We think this is how you could land Data Science Lead - Logistics in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with current Ocado employees on LinkedIn. A friendly chat can sometimes lead to opportunities that aren’t even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those related to logistics or machine learning. This will give you an edge and demonstrate your hands-on experience.
✨Tip Number 3
Prepare for interviews by brushing up on common data science questions and case studies. Practice explaining your thought process clearly, as collaboration is key in this role. We want to see how you tackle problems!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining the Ocado team.
We think you need these skills to ace Data Science Lead - 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 share specific examples that showcase your expertise!
Be a Team Player:Since collaboration is key for us, mention any experiences where you've worked effectively across different teams. Show us how you’ve led or mentored others, as we value a high-performing culture and want to know how you can contribute to it.
Keep It Pragmatic:We love a pragmatic approach! In your application, focus on quick outputs and iterative learning. Share instances where you've navigated ambiguity and delivered results in fast-paced environments—this will resonate with our mission.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. 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 machine learning and Python coding. Be ready to discuss your past projects and how you've built and deployed end-to-end solutions. This is your chance to showcase your technical prowess!
✨Show Off Your Leadership Skills
As a Data Science Lead, you'll need to demonstrate your ability to mentor and lead a team. Prepare examples of how you've coached team members in the past and fostered a high-performing culture. Highlight any experiences where you've successfully navigated ambiguity and delivered results.
✨Collaborate Like a Pro
Collaboration is key in this role, so be prepared to talk about how you've worked with product and engineering teams. Share specific instances where your collaborative mindset led to successful project outcomes. This will show that you're not just a lone wolf but a team player.
✨Think Outside the Box
Ocado Technology values innovative thinking, so come ready with ideas on how to leverage machine learning for business value. Think of potential proofs of concept you could propose and be ready to discuss how you'd approach integrating data science models into backend services.
