At a Glance
- Tasks: Join a dynamic team to develop and scale machine learning systems for ASOS.
- Company: ASOS is a leading online fashion retailer, empowering customers to express their true selves.
- Benefits: Enjoy employee discounts, personal development opportunities, flexible benefits, and 25 days paid leave.
- Why this job: Be part of innovative projects that impact millions while fostering a diverse and inclusive culture.
- Qualifications: Experience in machine learning, Python, and familiarity with deep learning frameworks required.
- Other info: Opportunities for publishing research and participating in hackathons are available.
The predicted salary is between 36000 - 60000 £ per year.
We are looking for an Applied Scientist to join one of our machine learning product teams and play a key role in helping ASOS provide the best shopping experience to our millions of customers. The role offers broad exposure to machine learning technologies at ASOS, requiring innovative solutions and close collaboration with business domains. The role sits within the Applied Science domain, which is responsible for the algorithms that power the ASOS digital ecosystem. The current focuses of these teams are Recommendations and Search, Marketing and Customer, Pricing and Forecasting; however, we are actively exploring new problem spaces. Each one of these teams drives key operating decisions. Our teams maintain, build and innovate in some of the most interesting areas of machine learning at scale, training models on unique datasets, transactions and clickstream data.
What Youll Be Doing
- You will be part of an agile, cross-functional team building and managing large-scale machine learning systems, working with massive amounts of data, and delivering models into production.
- You will be driving the implementation and scale-up of algorithms for measurable impact across the business and set up and conduct large-scale experiments to test hypotheses and drive product development.
- You will be keeping up to date with relevant state-of-the-art research, taking part in reading groups alongside other scientists, with the opportunity to publish novel prototypes for the business at top conferences.
- You will be continually developing and improving our code and technology, taking an active role in the conception of brand-new features for our millions of global customers.
- You will take part in regular Tech Develops days to learn new things, take part in internal and external hackathons, and share your knowledge and help drive improvements in science and engineering.
- You will support our culture by championing Diversity, Equity & Inclusion strategies.
About You
- You have professional experience in machine learning and their practical applications in production environments.
- Depending on the team we might expect you to have expertise in Bayesian statistics, deep learning, forecasting, causal methods, optimization and recommender systems.
- You are comfortable working in Python and familiar with at least one deep learning framework (e.g., PyTorch, TensorFlow).
- You have a solid understanding of software development lifecycles and engineering practices, alongside a good understanding of ML and statistics.
- You can work independently to manage projects and deliver prototypes against a timeline.
- The ability to work collaboratively and proactively in a fast-paced environment alongside both scientists, engineers, and non-technical stakeholders.
- We are keen to speak to people who are comfortable with R&D, and would love to meet someone who has authored publications in top-tier machine learning conferences or journals (e.g. NeurIPS, ICLR, ICML, KDD, CVPR, ICCV, ECCV, ACL, EMNLP).
BeneFITS
- Employee discount (hello ASOS discount!)
- ASOS Develops (personal development opportunities across the business)
- Employee sample sales
- Access to a huge range of LinkedIn learning materials
- 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
Want to find out how were tech powered? Check out the ASOS Tech Podcast here. Prefer reading? Check out our ASOS Tech Blog here.
Applied Scientist employer: Votre Sommelier
Contact Detail:
Votre Sommelier Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied Scientist
✨Tip Number 1
Familiarise yourself with the specific machine learning technologies and frameworks mentioned in the job description, such as PyTorch or TensorFlow. This will not only help you understand the role better but also allow you to speak confidently about your experience during interviews.
✨Tip Number 2
Engage with the ASOS community on social media platforms like LinkedIn or Twitter. Follow their tech teams and participate in discussions to show your enthusiasm for their work and culture, which can help you stand out as a candidate.
✨Tip Number 3
Consider contributing to open-source projects related to machine learning or even starting your own. This demonstrates your practical skills and commitment to the field, making you a more attractive candidate for the Applied Scientist position.
✨Tip Number 4
Prepare to discuss your past projects and any publications you've authored in detail. Be ready to explain the impact of your work and how it relates to the challenges faced by ASOS, showcasing your ability to drive measurable results.
We think you need these skills to ace Applied Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in machine learning, particularly in production environments. Emphasise any expertise you have in Bayesian statistics, deep learning, or recommender systems, as these are key areas for the role.
Craft a Compelling Cover Letter: In your cover letter, express your passion for machine learning and how it can enhance customer experiences. Mention specific projects or publications that demonstrate your skills and align with ASOS's focus on innovation and collaboration.
Showcase Relevant Projects: Include details of any relevant projects you've worked on, especially those involving large-scale machine learning systems or experiments. Highlight your role in these projects and the impact they had on the business or product development.
Research ASOS Culture: Familiarise yourself with ASOS's values, particularly their commitment to Diversity, Equity & Inclusion. Reflect this understanding in your application to show that you align with their culture and can contribute positively to their team.
How to prepare for a job interview at Votre Sommelier
✨Showcase Your Machine Learning Expertise
Be prepared to discuss your professional experience in machine learning, especially in production environments. Highlight specific projects where you've applied techniques like Bayesian statistics or deep learning, and be ready to explain the impact of your work.
✨Demonstrate Collaboration Skills
Since the role involves working closely with cross-functional teams, share examples of how you've successfully collaborated with both technical and non-technical stakeholders. Emphasise your ability to communicate complex ideas clearly and effectively.
✨Stay Updated on Current Research
Familiarise yourself with the latest trends and research in machine learning. Mention any recent papers or conferences that have inspired you, and be ready to discuss how these insights could apply to ASOS's projects.
✨Prepare for Technical Questions
Expect to face technical questions related to algorithms, coding, and data handling. Brush up on Python and any deep learning frameworks you're familiar with, and practice coding problems that may come up during the interview.