Senior Applied Scientist - Pricing

Job Description

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.

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 are looking for a Senior Applied Scientist to join a cross-functional AI team focused on pricing, customer targeting, and product optimization. This role involves developing cutting-edge algorithms using large-scale behavioral and transactional data, driving measurable impact across the business.

You will be instrumental in designing and deploying models that directly influence business strategy and customer experience, with opportunities to contribute to both academic research and real-world applications.

Key Responsibilities

• Design and implement advanced algorithms in the areas of pricing optimization, forecasting, and personalized targeting.
• Lead independent research and development (R&D) initiatives and prototype novel solutions based on state-of-the-art methodologies.
• Conduct rigorous large-scale experiments and statistical analyses to test and validate hypotheses.
• Write high-quality production-grade code and contribute to robust, scalable machine learning systems.
• Collaborate with technical and non-technical stakeholders to translate complex data insights into strategic business decisions.
• Mentor and coach junior scientists and engineers, supporting their technical development.
• Engage with the wider machine learning community, contribute to internal knowledge-sharing initiatives, and potentially publish at top-tier conferences.

Qualifications

• Proven experience in applied machine learning, with a strong grasp of statistics, regression techniques, ensemble models, and deep learning.
• Familiarity with optimization methods, causal inference, or reinforcement learning is a strong advantage.
• Proficiency in Python and at least one major deep learning framework.
• Experience working with distributed computing or training models at scale is a plus.
• Strong understanding of software development best practices, including version control, data engineering, and CI/CD workflows.
• Excellent communication skills, with the ability to engage effectively with both technical and non-technical stakeholders.
• Demonstrated ability to lead projects from concept to deployment.
• A track record of academic publications in machine learning conferences or journals is a bonus but not required.

Additional Information

• Competitive compensation and performance-based bonus
• Professional development opportunities across technical and leadership tracks
• Flexible working options and a supportive, inclusive work culture
• Generous annual leave and special occasion day
• Access to learning platforms and community events
• Health and wellbeing benefits
• Exclusive discounts and perks