ASOS.com
Applied Scientist

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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.
But how are we showing up? We’re proud members of Inclusive Companies, are Disability Confident Committed and have signed the Business in the Community Race at Work Charter and we placed 8th in the Inclusive Top 50 Companies Employer list.
Everyone needs some help showing up as their best self. Let our Talent team know if you need any adjustments throughout the process in whatever way works best for you.
Job Description
We're looking for an Applied Scientist to join the team – whose mission is to build machine learning capabilities that power better decisions, experiences and outcomes across ASOS.
You'll work on challenging real-world machine learning problems, developing scalable models and intelligent systems that support a range of business domains.
As an Applied Scientist, you'll work alongside data engineers, ML engineers, analysts, product managers and business stakeholders to design, develop and deploy machine learning solutions at scale. You'll have the opportunity to influence both the scientific direction of our ML capabilities and the products they enable.
Key Responsibilities
- Design, develop and deploy machine learning models and data-driven solutions in production environments.
- Apply machine learning and optimisation techniques to solve complex business problems.
- Partner with engineers to productionise models and build reliable, scalable ML systems.
- Design and analyse experiments and evaluation frameworks to measure model performance and business impact.
- Explore, evaluate and prototype new approaches from both industry and academia.
- Work closely with product and business stakeholders to identify opportunities where machine learning can create value.
- Contribute to the team's technical and scientific direction through knowledge sharing, code reviews and collaboration.
- Help shape best practices in machine learning, experimentation and applied research across the organisation.
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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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
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.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
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.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Qualifications
About You
You'll enjoy applying machine learning to large-scale, real-world challenges and translating research into production systems that deliver measurable impact.
We'd be particularly interested in candidates who bring experience in some of the following areas:
- Developing and deploying machine learning models in production environments.
- Applying statistics, analytics and machine learning techniques to solve complex business problems.
- Experience in one or more of the following areas:
- Developing and applying machine learning solutions to solve complex business problems.
- Building predictive models, intelligent systems or decision-support capabilities using large-scale data.
- Translating research, experimentation and analytical insights into production-ready solutions.
- Designing and evaluating models using appropriate performance, business and customer impact measures.
- Working across the end-to-end machine learning lifecycle, from problem definition and experimentation through to deployment and monitoring.
- Applying quantitative, statistical or optimisation techniques to support decision-making and product development.
- Proficiency in Python and modern machine learning frameworks such as PyTorch, TensorFlow or similar.
- Experience working with large datasets and distributed data processing systems.
- Strong software engineering practices, including testing, version control and maintainable code.
- Ability to communicate technical concepts to both technical and non-technical audiences.
- Curiosity, pragmatism and a willingness to learn, experiment and share knowledge.
- Experience bringing ML products from ideation through to production.
- Experience working in fast-paced, product-driven environments.
- Familiarity with cloud-native ML platforms and MLOps practices.
- Publications, open-source contributions or evidence of staying current with developments in machine learning and AI.


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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
- 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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