Data Science Lead β€” Commercial ML & Growth

Data Science Lead β€” Commercial ML & Growth

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

At a Glance

  • Tasks: Lead a talented data science team and design impactful ML solutions.
  • Company: Join IAG Loyalty, a leader in data-driven customer solutions.
  • Benefits: Competitive salary, flexible working, and opportunities for professional growth.
  • Other info: Dynamic team environment with a focus on innovation and collaboration.
  • Why this job: Shape the future of data science while making a real business impact.
  • Qualifications: Experience in data science and leadership skills required.

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

IAG Loyalty is seeking a commercially minded Data Science Lead to join the Data Products Leadership Team in London. You will lead a talented DS team, while remaining hands-on in designing and delivering production-ready ML solutions that solve core customer, marketing and commercial challenges.

You will partner with Product Owners, Engineers and business leaders, shaping the DS roadmap, prioritising high-value opportunities, and ensuring measurable business impact through experimentation.

Data Science Lead β€” Commercial ML & Growth employer: IAG Loyalty

IAG Loyalty is an exceptional employer, offering a dynamic work environment in Crawley where innovation and collaboration thrive. With a strong commitment to employee growth, we provide ample opportunities for professional development and leadership training, ensuring that our team members can shape their careers while contributing to a diverse holiday portfolio. Our inclusive culture fosters creativity and teamwork, making IAG Loyalty a rewarding place to work for those seeking meaningful impact in the travel industry.

IAG Loyalty

Contact Details:

IAG Loyalty Recruitment Team

We think you need these skills to ace Data Science Lead β€” Commercial ML & Growth

Communication Skills
Problem-Solving Skills
SQL
Python
Data Engineering
ETL/ELT Processes
Data Pipeline Development