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 comprehensive wellbeing support.
- Other info: Diverse team culture with excellent career growth opportunities.
- Why this job: Make a real impact with cutting-edge technology in a dynamic environment.
- Qualifications: Strong data science background and proven leadership skills 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.
What We’re Looking For
Essential
- 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.
Nice to Haves
- Experience with operational research and optimisation techniques.
- Experience in building and deploying Java backends and React frontends in a production environment.
Benefits
- 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 Group
Contact Detail:
Ocado Group Recruiting Team
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 with current employees at Ocado. A friendly chat can sometimes lead to job opportunities that aren't even advertised!
✨Tip Number 2
Show off your skills! Prepare a portfolio or a project that highlights your data science expertise, especially in logistics. This will give you an edge during interviews and show that you're ready to hit the ground running.
✨Tip Number 3
Practice makes perfect! Get comfortable with common interview questions for data science roles. Mock interviews with friends or using online platforms can help you articulate your thoughts clearly and confidently.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in being part of the Ocado team!
We think you need these skills to ace Data Science Manager - Logistics in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Data Science Manager role. Highlight your experience in leading teams and deploying machine learning solutions, as this will show us you’re a perfect fit for the job!
Show Off Your Skills: Don’t hold back on showcasing your Python coding skills and any relevant projects you've worked on. We love seeing practical examples of your work, so include links to your GitHub or any other portfolio that demonstrates your expertise.
Be Authentic: Let your personality shine through in your application. We value individuality and want to know what makes you unique. Share your experiences and how they’ve shaped your approach to data science and team leadership.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates about the hiring process!
How to prepare for a job interview at Ocado 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 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 Manager, you'll need to demonstrate your ability to lead and mentor a team. Prepare examples of how you've coached team members in the past and fostered 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 talk about how you've worked with product and engineering teams. Share specific instances where your collaborative mindset led to successful project outcomes. They want to see that you can bridge gaps and integrate data science models effectively.
✨Embrace Ambiguity
This position requires navigating technical and organisational ambiguity, so come ready to discuss how you've tackled challenges in fast-paced environments. Share examples of how you've iterated quickly and delivered pragmatic results, showing your curious nature and outside-the-box thinking.