Applied Scientist

Company: ASOS
Apply for the Applied Scientist
Location: London
Job Description:

We’re Disability Confident Committed – Let our Talent team know if you need any adjustments throughout the process in whatever way works best for you.

Job Description

We are seeking an Applied Scientist/Data Scientist to join a collaborative Customer and Marketing focused machine learning product team focused on delivering innovative solutions that enhance the customer experience. This role offers the opportunity to work on large-scale, real-world problems and contribute to impactful projects across key business areas.

The position is part of a function that designs and maintains algorithms supporting various operational and customer-facing domains – with a focus on Marketing focused Data Science/Machine Learning techniques. The team builds machine learning models at scale, drawing on rich data sources to drive meaningful outcomes.

Key Responsibilities

  • Collaborate within a cross-functional team to develop and deploy large-scale machine learning systems.
  • Working on marketing specific Data Science/Machine Learning projects
  • Lead the implementation and scaling of algorithms with measurable business impact.
  • Design and conduct experiments to validate models and inform product direction.
  • Stay current with developments in the field through research, reading groups, and prototype testing.
  • Contribute to ongoing improvements in code quality, infrastructure, and feature development.
  • Participate in learning opportunities, knowledge-sharing sessions, and technical events.
  • Promote diversity, equity, and inclusion in both team culture and work practices.

Qualifications

About You

  • Demonstrated experience applying machine learning in production environments.
  • An interest in working on marketing specific Data Science/Machine Learning projects – Such as MMM, Incrementality/Causal Inference etc.
  • Depending on the team’s focus, relevant experience could include areas such as causal inference, or Bayesian methods.
  • Proficiency in programming languages used in machine learning and familiarity with common frameworks.
  • Solid grasp of statistical methods and software development best practices.
  • Ability to work independently, manage timelines, and deliver prototypes or models aligned with business needs.
  • Strong collaboration skills and comfort working across technical and non-technical roles.
  • An interest in research and innovation, with any publications in reputable machine learning venues considered a plus.

Additional Information

  • Employee sample sales
  • 25 days paid annual leave + an extra celebration day for a special moment
  • Private medical care scheme
  • Fixed Annual Payment in addition to your salary each year, it’s just an extra thank you from us
  • Opportunity for personalised learning and in-the-moment experiences that enable you to thrive and excel in your role.

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Posted: April 22nd, 2026