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- Tasks: Lead a team to develop AI systems for optimising logistics and planning.
- Company: Join Ocado Technology, revolutionising shopping with cutting-edge tech.
- Benefits: Enjoy hybrid working, competitive salary, and extensive wellbeing support.
- Other info: Diverse and inclusive workplace with excellent career growth opportunities.
- Why this job: Make a real impact in logistics with innovative AI solutions.
- Qualifications: Strong data science background and proven leadership skills required.
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.
Our employee benefits are designed for you, we care about people and we’ve ensured we have a wealth of benefits that focus on your well‑being. We regularly review our benefits to ensure we are supporting our employees appropriately. Currently, we offer technically stretching work, a competitive salary.
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)
Be bold, be unique, be brilliant, be you. 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 employer: Ocado Technology Group
Contact Detail:
Ocado Technology Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Science Lead - Logistics
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects, especially those related to logistics and machine learning. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by practising common data science questions and case studies. Get comfortable explaining your thought process and how you approach problem-solving, as this is key for roles like Data Science Lead.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Data Science Lead - Logistics
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your 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 mentoring 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 and iterative learning. This shows us you're ready to navigate the fast-paced environment we thrive in.
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 hear from you!
How to prepare for a job interview at Ocado Technology Group
✨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 deployed end-to-end solutions. This is your chance to showcase your technical prowess!
✨Showcase 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 how you foster a high-performing culture. Highlight your experience in managing diverse teams and driving best practices.
✨Collaborate Like a Pro
Collaboration is key in this role, so be prepared to discuss how you've worked with product and engineering teams in the past. Share specific examples of successful integrations of data science models into backend services and how you navigated any challenges.
✨Embrace Ambiguity
This position requires a pragmatic approach to delivery in a fast-paced environment. Be ready to talk about times when you've tackled ambiguity and delivered results. Show your curiosity and willingness to think outside the box to solve complex problems.