ASOS
Senior Applied Scientist

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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.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
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.


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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
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