Head of Data Science & Personalisation - Hybrid London

Head of Data Science & Personalisation - Hybrid London

London Full-Time 80000 - 100000 Β£ / year (est.) No working from home possible
Data Idols

At a Glance

  • Tasks: Lead a team to shape machine learning strategies for personalised experiences.
  • Company: Data Idols, a forward-thinking company in London.
  • Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
  • Other info: Collaborative environment with a focus on innovation and analytics.
  • Why this job: Make a real impact by translating data into actionable insights.
  • Qualifications: Experience in data science and strong leadership skills.

The predicted salary is between 80000 - 100000 Β£ per year.

Data Idols in London is seeking a Data Science Manager to lead the team and shape the machine learning strategy that powers personalised experiences at scale. You will translate complex customer data into clear, actionable recommendations and drive the roadmap for experimentation, customer modelling, and MLOps.

You will establish best practices for data science delivery and work to grow the organisation's analytics capabilities while collaborating with business stakeholders to align data-powered initiatives.

Head of Data Science & Personalisation - Hybrid London employer: Data Idols

Data Idols is an exceptional employer for those looking to make a significant impact in the tech industry. With a hybrid work model in vibrant London, employees enjoy a collaborative culture that fosters innovation and creativity, alongside ample opportunities for professional growth and development. Join us to tackle complex machine learning challenges while being part of a forward-thinking team dedicated to shaping the future of technology.

Data Idols

Contact Details:

Data Idols Recruitment Team

We think you need these skills to ace Head of Data Science & Personalisation - Hybrid London

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