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- Tasks: Join a team to develop and deploy innovative machine learning solutions for enhancing customer experience.
- Company: ASOS, a leading online fashion retailer committed to inclusivity and creativity.
- Benefits: Enjoy employee discounts, 25 days annual leave, private medical care, and more.
- Why this job: Make a real impact on customer experience while working with cutting-edge technology.
- Qualifications: Experience in machine learning, programming skills, and a passion for research and innovation.
- Other info: Collaborative environment with a focus on diversity, equity, and inclusion.
The predicted salary is between 36000 - 60000 £ per year.
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.
We are seeking an Applied Scientist to join a collaborative 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 broader Applied Science function that designs and maintains algorithms supporting various operational and customer-facing domains. 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.
- 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.
- Demonstrated experience applying machine learning in production environments.
- 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.
- 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
Applied Scientist (Marketing & Customer) in London employer: ASOS.com
Contact Detail:
ASOS.com Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied Scientist (Marketing & Customer) in London
✨Tip Number 1
Network like a pro! Reach out to current ASOS employees on LinkedIn, join relevant groups, and attend industry events. Building connections can give you insider info and might just land you a referral.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects and experiments. This is your chance to demonstrate your expertise and creativity, so make it shine!
✨Tip Number 3
Prepare for the interview by brushing up on your technical knowledge and soft skills. Practice common interview questions and think about how your experience aligns with ASOS's values of diversity and inclusion.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the ASOS family.
We think you need these skills to ace Applied Scientist (Marketing & Customer) in London
Some tips for your application 🫡
Show Your True Self: When writing your application, don’t hold back! We want to see the real you, so let your personality shine through. Share your unique experiences and how they relate to the role – it’s all about being authentic!
Tailor Your Application: Make sure to customise your application for the Applied Scientist role. Highlight your relevant experience in machine learning and how it can impact our customer experience. We love seeing how your skills align with what we do!
Be Clear and Concise: Keep your application straightforward and to the point. Use clear language and avoid jargon where possible. We appreciate a well-structured application that makes it easy for us to see your qualifications and enthusiasm.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy – just follow the prompts!
How to prepare for a job interview at ASOS.com
✨Know Your Machine Learning Stuff
Make sure you brush up on your machine learning concepts, especially those relevant to the role like causal inference and Bayesian methods. Be ready to discuss your past experiences applying these techniques in production environments, as this will show your practical knowledge.
✨Show Off Your Collaboration Skills
Since this role involves working within a cross-functional team, be prepared to share examples of how you've successfully collaborated with both technical and non-technical colleagues. Highlight any projects where teamwork led to innovative solutions or improved outcomes.
✨Bring Your Creativity to the Table
ASOS values creativity, so think about how you can demonstrate your innovative thinking during the interview. Prepare to discuss any unique approaches you've taken in past projects or how you've contributed to enhancing customer experiences through your work.
✨Stay Current and Curious
Show your passion for the field by discussing recent developments in machine learning that excite you. Mention any research, reading groups, or prototype testing you've been involved in, as this will reflect your commitment to continuous learning and improvement.
