Data Scientist

Ocado; Greater London; Hybrid; GBP 70,000 - 110,000; Full time

Benefits offered by this job

25 days annual leave

Private Medical Insurance

Pension with employer matching up to 7

Cycle to Work Scheme

Shuttle buses

Ocado discounts

Job summary

Ocado is seeking a Data Scientist in London to power its Logistics and Fulfilment ML stack within a hybrid work model. You will own end-to-end data science—from research to deploying production-ready models—supporting demand forecasting, drive-time predictions, and supplier reliability for global partners.

You will work closely with eng, data engineering, and product teams to refine architectures, build robust pipelines, and maintain scalable solutions that impact operations and revenue.

Qualifications

• Proven experience with Python and SQL in a production setting.
• Experience with Google Cloud Platform (GCP).
• 2+ years in data science focused on productionising models, or 2+ years in software/data engineering with ML studies.
• Strong understanding of ML fundamentals and modern software development practices (CI/CD, testing, docs).
• Ability to communicate complex results to non-technical stakeholders.

Responsibilities

• Improve model architectures for operational challenges and scale for global partners.
• Build scalable data pipelines feeding ML models with high-quality data.
• Manage production ML models ensuring availability and performance.
• Collaborate with product and software teams to deploy ML solutions.

Skills

Python

SQL

GCP

Production ML

CI/CD

Documentation

Tools

TensorFlow

Keras

Job description

Data Scientist | Logistics & Fulfilment | Hybrid Working | London

Introduction:

We are Ocado Group, and we're bringing world-class automation to online grocery. Our Ocado Smart Platform (OSP) combines cutting-edge robotics, AI, and IoT within our advanced CFCs (Customer Fulfilment Centres). We've mastered the single pick, transforming online delivery for our global partners. Join us and be part of a team pushing the boundaries of retail technology.

About the Role

As a Data Scientist in our Treefrogs team, you will play a key role in powering the machine learning algorithms behind Ocado Group’s Logistics and Supply Chain technology. Our mission-critical models drive key operational decisions for global partners, including demand forecasting, drive-time predictions, and supplier reliability. In this role, you will own the full data science lifecycle, from researching state-of-the-art deep learning techniques to deploying, scaling, and supporting production-ready models.

Working closely with cross-functional software engineering, data engineering, and product teams, you will tackle high-impact problems where algorithm performance directly affects operational efficiency and partner revenue. You will continuously refine existing architectures, build robust data pipelines, and explore new applications for machine learning, ensuring our systems remain reliable, scalable, and cutting-edge.

Key Responsibilities

• Improve existing model architectures and adapt them to solve new operational challenges and support global partner expansions.
• Design and build scalable data pipelines to feed richer, high-quality data into machine learning models.
• Own, support, and maintain machine learning models in production environments, ensuring high availability and performance.
• Collaborate with Product teams to identify, define, and build new machine learning applications across our stream.
• Work alongside Software Engineering teams to design robust interfaces between machine learning models and broader software systems.
• Communicate complex technical findings and model performance clearly to both internal and external stakeholders.
• Promote and uphold best practices in machine learning development, testing, and continuous deployment.
• Stay up to date with the latest machine learning research to identify and implement innovative techniques.

What We’re Looking For

Essential

• Strong programming proficiency in Python and solid knowledge of SQL.
• Practical experience working with Google Cloud Platform (GCP).
• Either 2+ years of data science experience with an emphasis on productionising models, OR 2+ years in a software/data engineering role with formal study in machine learning.
• Good comprehension of fundamental machine learning concepts.
• Familiarity with modern software development processes, including code reviews, CI/CD, testing, and documentation.
• Ability to document and explain technical concepts clearly to non-technical audiences.

Nice to Haves

• Experience with deep learning frameworks such as TensorFlow or Keras.
• Knowledge of time-series modelling techniques, particularly transformers.
• Experience working with geospatial data and geospatial modelling techniques.

Benefits

We believe in supporting our people with meaningful, flexible benefits that prioritise well-being and work-life balance. Here’s a snapshot of what you can expect:

• Time to recharge: 25 days annual leave (rising to 27 after 5 years), plus the option to buy more - and 30 days a year to work from anywhere in the world.
• Health & wellbeing: Private Medical Insurance from your first month, wellbeing support through specialist apps and EAP, plus Income Protection and Life Assurance.
• Family-first policies: 22 weeks paid maternity/primary carer leave and 6 weeks paid paternity leave
• Financial support: Pension with employer matching up to 7%, share schemes (Sharesave & BAYE), and interest-free loans for train tickets.
• Commuter perks: Cycle to Work Scheme and free shuttle buses to/from Hatfield and Welwyn Garden City stations.
• Exclusive discounts: 15% off at Ocado.com with free delivery (starting in your first month).

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.