Data Scientist – Production ML for Global Logistics in City of Westminster

Data Scientist – Production ML for Global Logistics in City of Westminster

City of Westminster Full-Time 63000 - 77000 Β£ / year (est.) No working from home possible
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At a Glance

  • Tasks: Own end-to-end ML development for logistics and supply chain tech.
  • Company: Join Ocado Group, a leader in innovative logistics solutions.
  • Benefits: Competitive salary, flexible working, and opportunities for professional growth.
  • Other info: Collaborative team environment with exciting challenges and career advancement.
  • Why this job: Make a real impact on global logistics with cutting-edge machine learning.
  • Qualifications: Experience in machine learning and data pipeline design.

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

Ocado Group in the United Kingdom seeks a Data Scientist for the Treefrogs team to own end-to-end ML development for logistics and supply chain tech, including demand forecasting and drive-time predictions. You will design scalable data pipelines, deploy models to production, collaborate with cross-functional teams, and stay at the forefront of ML research to drive operational efficiency and partner value.

Data Scientist – Production ML for Global Logistics in City of Westminster employer: Ocado Group

At Ocado Logistics, we pride ourselves on being an exceptional employer, offering a vibrant work culture where every team member plays a crucial role in delivering outstanding customer experiences. With flexible part-time hours, competitive pay including paid breaks, and a comprehensive benefits package tailored to your lifestyle, we ensure that our employees feel valued and supported. Join us in Luton, where you'll enjoy a friendly atmosphere, opportunities for personal growth, and the chance to make a real difference in people's lives every day.

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Contact Details:

Ocado Group Recruitment Team

We think you need these skills to ace Data Scientist – Production ML for Global Logistics in City of Westminster

Machine Learning
Data Pipeline Design
Model Deployment
Demand Forecasting
Drive-Time Predictions
Collaboration with Cross-Functional Teams
Operational Efficiency