Hybrid Logistics Data Science Manager β€” Global Planning

Hybrid Logistics Data Science Manager β€” Global Planning

Full-Time 60000 - 75000 Β£ / year (est.) No working from home possible
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At a Glance

  • Tasks: Lead the Autoplanner team and deliver AI-driven logistics planning.
  • Company: Ocado Technology, a leader in innovative logistics solutions.
  • Benefits: Hybrid work model, competitive salary, and opportunities for mentorship.
  • Other info: Dynamic role with opportunities for professional growth across locations.
  • Why this job: Make a real impact in global logistics with cutting-edge AI technology.
  • Qualifications: Experience in data science and leadership skills required.

The predicted salary is between 60000 - 75000 Β£ per year.

Ocado Technology in London and Hatfield is seeking a Data Science Manager for Logistics to lead the Autoplanner team and deliver AI-enabled planning across global warehouses.

You will bridge research and live operations, integrating models into backend services and scaling a high performing team.

You will mentor and coach engineers and scientists, drive best practices, and deliver systems that balance profitability with operational excellence.

This hybrid role spans London and Hatfield.

Hybrid Logistics Data Science Manager β€” Global Planning employer: 3M HEALTHCARE

Ocado Technology is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of London and Hatfield. With a strong focus on employee growth, you will have the opportunity to mentor and lead a talented team while working on cutting-edge AI solutions that drive operational excellence. The hybrid nature of this role allows for flexibility, ensuring a healthy work-life balance as you contribute to impactful projects in a forward-thinking environment.

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Contact Details:

3M HEALTHCARE Recruitment Team

We think you need these skills to ace Hybrid Logistics Data Science Manager β€” Global Planning

Communication Skills
Python
SQL
Problem-Solving Skills
Automation
Attention to Detail
Data Engineering