Data Scientist in London

Data Scientist in London

London Full-Time 63000 - 77000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Join our Treefrogs team to power machine learning algorithms for logistics and supply chain.
  • Company: Ocado Group, a leader in online grocery automation with cutting-edge technology.
  • Benefits: Enjoy 25 days annual leave, private medical insurance, and flexible working options.
  • Other info: Diverse and inclusive workplace with excellent career growth opportunities.
  • Why this job: Make a real impact on global operations while working with innovative tech.
  • Qualifications: Strong Python skills, experience in data science or software engineering, and knowledge of machine learning.

The predicted salary is between 63000 - 77000 £ per year.

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 Io T 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 Tensor Flow 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.

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Data Scientist in London employer: Jackalope Digital LLC

MoonPay is an exceptional employer that fosters a dynamic and collaborative work culture in the heart of London. With a strong emphasis on employee growth, you will have the opportunity to lead innovative projects in real-time fraud detection while working alongside talented professionals. The company offers competitive benefits and a commitment to high-velocity delivery, making it an ideal place for those seeking meaningful and rewarding employment.

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Contact Details:

Jackalope Digital LLC Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Data Scientist in London

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Jackalope Digital LLC!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Scientist at Jackalope Digital LLC.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Jackalope Digital LLC.

Apply Directly through Our Website

When you find a suitable opening like Data Scientist at Jackalope Digital LLC, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Data Scientist in London

Python
SQL
Google Cloud Platform (GCP)
Machine Learning
Deep Learning
TensorFlow
Keras

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Jackalope Digital LLC, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Jackalope Digital LLC. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Jackalope Digital LLC

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Jackalope Digital LLC!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.