Staff Data Scientist: Growth & Personalization Leader in London

Staff Data Scientist: Growth & Personalization Leader in London

London Full-Time 70000 - 90000 Β£ / year (est.) No working from home possible
Dex

At a Glance

  • Tasks: Drive data strategy and optimise user incentives using ML models.
  • Company: Fast-growing tech company with millions of users.
  • Benefits: Competitive salary, mentorship opportunities, and a vibrant office culture.
  • Other info: Join a dynamic team in London with excellent growth potential.
  • Why this job: Make a real impact in a high-stakes role while mentoring the next generation.
  • Qualifications: Extensive experience in ML model deployment and strong leadership skills.

The predicted salary is between 70000 - 90000 Β£ per year.

Dex is seeking a highly skilled Staff Data Scientist to drive data strategy and optimize user incentives. You will design and deploy ML models in a fast-growing company that has scaled to millions of users.

The ideal candidate has extensive experience in deploying ML models, advanced statistical modeling, and strong leadership in a cross-functional environment. Work will take place in the London office, ensuring a high-impact role with the potential to mentor junior talent.

Staff Data Scientist: Growth & Personalization Leader in London employer: Dex

At Dex, we pride ourselves on being an exceptional employer that fosters innovation and collaboration in our London office. Our vibrant work culture encourages creativity and offers ample opportunities for professional growth, including mentorship roles for experienced staff like the Staff Data Scientist. With a commitment to employee development and a focus on impactful projects, Dex is the perfect place for those looking to make a meaningful contribution in a fast-paced environment.

Dex

Contact Details:

Dex Recruitment Team

We think you need these skills to ace Staff Data Scientist: Growth & Personalization Leader in London

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