Product Data Scientist - Recommendation Systems

Product Data Scientist - Recommendation Systems

Full-Time 90000 - 90000 £ / year (est.) No working from home possible
Harnham

At a Glance

  • Tasks: Own product decisions and build AI-powered customer experiences from concept to production.
  • Company: Join a leading online marketplace with a strong focus on data innovation.
  • Benefits: Competitive salary up to £90K, hybrid work model, and opportunities for professional growth.
  • Other info: Work in a collaborative environment with a focus on innovation.
  • Why this job: Combine Data Science, Product, and Commercial impact in a dynamic role.
  • Qualifications: Experience in data science and a passion for product development.

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

Want to own product decisions rather than just analyse them?

Interested in building AI-powered customer experiences from idea to production?

Looking for a role where Data Science, Product and Commercial impact genuinely come together?

Brighton | Hybrid (3 days in office) | Up to £90K I'm partnering with one of the world's leading online marketplaces, currently investing heavily in Data

Product Data Scientist - Recommendation Systems employer: Harnham

Join a leading UK-based media organisation at the forefront of digital transformation, where your role as Director of Streaming Product and Growth will be pivotal in shaping the future of their subscription services. With a strong emphasis on innovation and a collaborative work culture, you'll have access to significant growth opportunities, competitive salary packages, and a performance-based bonus structure, all while working in a dynamic environment that values data-driven decision making and customer-centric strategies.

Harnham

Contact Details:

Harnham Recruitment Team

We think you need these skills to ace Product Data Scientist - Recommendation Systems

Data Science
AI-Powered Solutions
Product Decision-Making
Customer Experience Design
Analytical Skills
Machine Learning
Statistical Analysis