At a Glance
- Tasks: Lead the evolution of Applied Science operating models and promote AI-enabled practices.
- Company: Join ASOS, a forward-thinking company embracing AI and innovation.
- Benefits: Competitive salary, flexible working, mentorship opportunities, and a vibrant community.
- Other info: Be part of a dynamic team driving AI transformation across the business.
- Why this job: Shape the future of AI in a collaborative environment and make a real impact.
- Qualifications: Strong background in applied science, leadership skills, and a passion for AI.
The predicted salary is between 80000 - 98000 £ per year.
AI platform enablement Federated operating model governance GenAI-enabled ways of working. Today, Applied Science expertise exists across multiple business domains, including recommendations, forecasting, pricing, consumer modelling and marketing measurement. While this structure enables close alignment with business needs, it can also create opportunities for greater consistency, collaboration and reuse across teams. In this role, you'll help establish the operating model, standards and technical direction that enable Applied Science teams to deliver impact at scale while maintaining flexibility within their domains. This is a highly collaborative leadership role that combines technical expertise, systems thinking, stakeholder partnership and the ability to translate strategy into practical outcomes.
What you'll be doing
- Applied Science Operating Model Leadership
- Define and evolve the Applied Science operating model across federated business domains.
- Establish shared approaches for model development, evaluation, experimentation, deployment and monitoring.
- Promote the adoption of common tooling, reusable components and MLOps best practices.
- Develop governance frameworks that support consistency while enabling teams to move effectively within their domains.
- Encourage reuse of AI capabilities and platform components to reduce duplication and accelerate delivery.
- AI Platform & Product Enablement
- Partner with Data Platform and Engineering teams to help shape the Applied Science platform roadmap.
- Support the prioritisation and simplification of platform requirements across science teams.
- Promote reusable frameworks, feature stores, evaluation capabilities and deployment standards.
- Foster a strong Applied Science community through technical forums, shared practices and knowledge exchange.
- Support the growth of scientific capability through mentorship, technical review and inclusive hiring practices.
- Work with senior stakeholders across Product, Technology, Commercial and Operations to align priorities and drive business impact.
- Community & Technical Leadership
- Help build and strengthen the Applied Science community across ASOS.
- Establish forums, review practices and knowledge-sharing mechanisms that encourage collaboration and learning.
- Mentor scientists and support the continuous improvement of technical and scientific practices.
- Contribute to hiring processes and help develop consistent approaches to technical assessment.
- Partner with stakeholders across Product, Technology, Commercial and Operations to align on opportunities and priorities.
- Support the adoption of GenAI, AI-assisted tooling and emerging AI-powered ways of working across the Applied Science lifecycle.
- Explore opportunities to improve experimentation, feature engineering, model evaluation, documentation and development workflows through AI-enabled approaches.
- Identify where AI assistants and autonomous workflows can improve efficiency and productivity.
- Collaborate with Engineering and Product teams to shape AI-native ways of working.
- Strategic AI Leadership
- Contribute to the development of ASOS's broader AI strategy and transformation agenda.
- Help translate successful models and experiments into scalable enterprise capabilities.
- Contribute to long-term thinking around agentic commerce, personalisation and AI-enabled operating models.
- Clearly communicate scientific strategy, opportunities and outcomes to senior and executive stakeholders.
ASOS is evolving towards an AI-enabled operating model where intelligence, automation and AI-powered workflows increasingly shape how we trade, forecast, personalise experiences and operate at scale. We see AI not as a standalone capability, but as a foundational part of how we serve customers, make decisions and run our business.
StudySmarter Expert Advice🤫
We think this is how you could land Principal Applied Scientist in City of Westminster
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like asos.com Ltd!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Principal Applied Scientist at asos.com Ltd.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like asos.com Ltd.
✨Apply Directly through Our Website
When you find a suitable opening like Principal Applied Scientist at asos.com Ltd, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Principal Applied Scientist in City of Westminster
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at asos.com Ltd, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at asos.com Ltd. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at asos.com Ltd
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at asos.com Ltd!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
