Lead Data Scientist — Strategy & ML Leadership (Hybrid) in Leeds

Lead Data Scientist — Strategy & ML Leadership (Hybrid) in Leeds

Leeds Full-Time 60000 - 80000 £ / year (est.) No working from home possible

At a Glance

  • Tasks: Lead a team to deliver impactful data science solutions and drive commercial value.
  • Company: Join Jet2.com, a dynamic leader in the travel industry.
  • Benefits: Enjoy a hybrid work model, competitive salary, and career development opportunities.
  • Other info: Be part of a vibrant team in Leeds City Centre.
  • Why this job: Shape the future of data science while making a real impact in the travel sector.
  • Qualifications: Proven experience in data science and leadership skills.

The predicted salary is between 60000 - 80000 £ per year.

Jet2. com is seeking a Lead Data Scientist based in Leeds for a hybrid role at Holiday House in Leeds City Centre.

You will lead a team delivering data science solutions that drive commercial value across the Jet2 business and work with stakeholders to identify opportunities for data-driven decision-making.

Responsibilities include leading projects end-to-end, deploying models in production, and shaping the future of data science within the Jet2 group.

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Lead Data Scientist — Strategy & ML Leadership (Hybrid) in Leeds employer: 慨正橡扯

At 慨正橡扯, we pride ourselves on being an exceptional employer that champions innovation and collaboration in the field of Behavioral Economics and Retirement Research. Our hybrid working model not only offers flexibility but also nurtures a vibrant work culture where employees are encouraged to grow and develop their skills through meaningful projects and leadership opportunities. Join us in Europe, where your expertise will directly contribute to enhancing investor outcomes and shaping impactful business strategies.

Contact Details:

慨正橡扯 Recruitment Team

We think you need these skills to ace Lead Data Scientist — Strategy & ML Leadership (Hybrid) in Leeds

Data Science
Machine Learning
Team Leadership
Stakeholder Engagement
Project Management
Model Deployment
Data-Driven Decision Making