Senior Applied Scientist

Posted 8 Days Ago
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London, England, GBR
Hybrid
Senior level
eCommerce • Retail
The Role
Lead the design, development, evaluation, and deployment of scalable machine learning solutions for complex business challenges. Identify high-value AI opportunities, improve model performance and reliability, research emerging techniques, and create robust evaluation frameworks. Partner with ML and data engineers, product teams, analysts, and business stakeholders to deliver production-ready solutions. Provide technical leadership, mentor scientists, communicate recommendations, and apply software engineering best practices.
Summary Generated by Built In
Company Description

We're ASOS, the online retailer for fashion lovers all around the world. 

We exist to give our customers the confidence to be whoever they want to be, and that goes for our people too. At ASOS, you're free to be your true self without judgement, and channel your creativity into a platform used by millions. 

Everyone needs some help showing up as their best self. We're Disability Confident Committed - let our Talent team know if you need any reasonable adjustments throughout the recruitment process 

Job Description

We're looking for a Senior Applied Scientist to join the team – whose mission is to build machine learning capabilities that power critical business decisions, products and customer experiences across ASOS.

You'll work on complex, high-impact machine learning challenges, developing scalable solutions that can be applied across a range of business domains. As we continue to expand our AI capabilities, you'll play a key role in shaping scientific approaches, identifying new opportunities for machine learning, and translating research into practical solutions that deliver measurable value.

As a Senior Applied Scientist, you'll provide technical leadership across initiatives, partnering closely with ML Engineers, Data Engineers, Analysts, Product Managers and business stakeholders to design, develop and deploy machine learning solutions at scale. You'll help shape both our scientific direction and the machine learning capabilities that underpin our products and decision-making.

Responsibilities

  • Lead the design, development and evaluation of machine learning solutions for complex business challenges.
  • Identify opportunities where machine learning can create measurable value.
  • Drive improvements in model performance, scalability, reliability and operational impact across a range of use cases.
  • Research, evaluate and prototype emerging approaches from industry and academia, identifying opportunities to enhance existing capabilities.
  • Design robust evaluation frameworks to assess model quality, customer outcomes and business impact.
  • Write, test and maintain production-quality code, applying software engineering best practices to support scalable and maintainable solutions.
  • Partner closely with ML Engineers and Data Engineers to ensure solutions can be deployed and operated effectively at scale.
  • Provide technical leadership on complex initiatives, influencing scientific direction and technical decision-making.
  • Mentor and support other scientists through coaching, code reviews, knowledge sharing and technical guidance.
  • Communicate complex technical concepts and recommendations clearly to both technical and non-technical stakeholders.

Qualifications

You'll likely bring experience in some of the following areas:

  • Developing and deploying machine learning solutions in production environments.
  • Applying machine learning techniques to solve complex real-world problems.
  • Leading the design and evaluation of data-driven solutions that deliver measurable business value.
  • Developing new approaches or adapting research and emerging technologies to practical business challenges.
  • Working across the end-to-end machine learning lifecycle, from problem definition and experimentation through to deployment and monitoring.
  • Proficiency in Python and modern machine learning frameworks such as PyTorch, TensorFlow or similar technologies.
  • Experience working with large datasets and distributed data processing environments.
  • Applying software engineering best practices including testing, version control and developing maintainable, reproducible code.
  • Collaborating effectively with engineers, product teams and business stakeholders to deliver production-ready solutions.
  • Communicating complex technical concepts clearly to technical and non-technical audiences.
  • Providing technical leadership, mentoring others and influencing scientific direction across projects.
  • Curiosity, pragmatism and sound judgement when balancing innovation with business outcomes.

Additional Information

BeneFITS’ 

  • Employee discount (hello ASOS discount!) 
  • Employee sample sales 
  • 25 days paid annual leave + an extra celebration day for a special moment 
  • Discretionary bonus scheme 
  • Private medical care scheme 
  • Flexible benefits allowance - which you can choose to take as extra cash, or use towards other benefits 
  • Opportunity for personalised learning and in-the-moment experiences that enable you to thrive and excel in your role 

Skills Required

  • Experience developing and deploying machine learning solutions in production environments
  • Experience applying machine learning techniques to complex real-world problems
  • Experience leading the design and evaluation of data-driven solutions delivering measurable business value
  • Experience developing or adapting research and emerging technologies for practical business challenges
  • Experience across the end-to-end machine learning lifecycle, including experimentation, deployment, and monitoring
  • Proficiency in Python and modern machine learning frameworks such as PyTorch or TensorFlow
  • Experience working with large datasets and distributed data processing environments
  • Experience applying software engineering best practices, including testing, version control, and maintainable reproducible code
  • Experience collaborating with engineers, product teams, and business stakeholders to deliver production-ready solutions
  • Ability to communicate complex technical concepts to technical and non-technical audiences
  • Experience providing technical leadership, mentoring others, and influencing scientific direction

ASOS Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about ASOS and has not been reviewed or approved by ASOS.

  • Wellbeing & Lifestyle Benefits Feedback suggests perks like a sizable, shareable product discount, access to sample sales, free gym access, and on-site amenities are valued. Such lifestyle-oriented benefits are frequently highlighted as standout aspects of the package.
  • Leave & Time Off Breadth Feedback suggests employees benefit from substantial annual leave with bank holidays and an extra celebratory or birthday day off, with summer early finishes referenced in some contexts. This breadth of time-off options supports work-life balance.
  • Healthcare Strength Feedback suggests access to a private medical care scheme is a core part of the package. This contributes to a perception of strong healthcare support.

ASOS Insights

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The Company
HQ: London
3,200 Employees
Year Founded: 2000

What We Do

We exist to give people the confidence to be whoever they want to be, and that goes for our people too. At ASOS, you’re free to be your true self without judgment, and channel your creativity into a platform used by millions. Whatever your role, asos will encourage you to be you, fulfilling your creative potential with our global reach. Push boundaries, and challenge expectations. We’re determined to succeed, so we’ll trust you to deliver. Help drive our journey to becoming the global fashion destination for 20-somethings At ASOS our 3,000+ employees are immersed in the creative worlds and have a truly entrepreneurial attitude. Our ASOSers are authentic, brave, creative and disciplined to the core and find ways to blend our passion for fashion with cutting edge technology. Sound up your street? Join us.

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