Senior Applied Scientist

Senior Applied Scientist

Full-Time 63000 - 77000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Lead the design and development of advanced machine learning models for demand forecasting.
  • Company: Join ASOS, a global fashion retailer that celebrates creativity and individuality.
  • Benefits: Enjoy employee discounts, flexible benefits, and 25 days of annual leave plus a bonus day.
  • Other info: Collaborative environment with opportunities for mentorship and personal growth.
  • Why this job: Shape the future of AI in fashion while making a real impact on business decisions.
  • Qualifications: Experience in machine learning, Python, and statistical methods is essential.

The predicted salary is between 63000 - 77000 £ 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.

Everyone needs some help showing up as their best self.

We're Disability Confident Committed - let our Talent team know if you need any reasonable adjustments throughout the recruitment process

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.

Everyone needs some help showing up as their best self.

We're Disability Confident Committed - let our Talent team know if you need any reasonable adjustments throughout the recruitment process

Job Description

We're looking for a Senior Applied Scientist to join our AI Demand Forecasting team.

Our mission is to build forecasting capabilities that power critical business decisions across the company.

While our foundations are in replenishment forecasting, we're evolving into a forecasting platform that provides scalable, high-quality demand forecasts for a growing range of use cases, including AI-powered Pricing and Supply Chain Optimisation.

This means solving complex machine learning challenges while developing reusable forecasting capabilities that can be applied across multiple business domains.

As a Senior Applied Scientist, you'll help shape the scientific direction of our forecasting platform, leading the design of advanced machine learning solutions that combine statistical modelling, deep learning and multimodal AI to solve challenging forecasting problems.

You'll work closely with ML Engineers, data engineers, analysts, product managers and business stakeholders to translate research into production systems and create measurable business impact.

Responsibilities

  • Lead and collaborate on the design, development and evaluation of machine learning models for demand forecasting and related AI products.
  • Shape and support improvements in forecasting accuracy, robustness, scalability and explainability across multiple business domains.
  • Develop reusable modelling approaches that support a growing forecasting platform serving replenishment, pricing, supply chain optimisation and future AI products.
  • Research, prototype and evaluate modern and emerging machine learning techniques from academia and industry, identifying opportunities to improve forecasting performance.
  • Design rigorous offline and online evaluation methodologies to measure both model quality and business impact.
  • Write, test and maintain production-quality Python code for machine learning models and forecasting pipelines, following software engineering best practices to support reliable deployment and long-term maintainability.
  • Work closely with ML Engineers to productionise models, ensuring scientific approaches can operate reliably and efficiently at scale.
  • Provide technical leadership and guidance on complex modelling projects, helping shape scientific direction and investment decisions.
  • Mentor and support other scientists through technical guidance, code reviews, experimentation best practices and knowledge sharing.
  • Communicate scientific findings and recommendations clearly to both technical and non-technical stakeholders.

Qualifications

You’ll be excited by solving complex machine learning challenges, advancing forecasting capabilities and seeing innovative research translated into measurable business impact.

We're interested in people with a range of experiences and backgrounds.

If your experience doesn't align perfectly with every qualification below, we'd still encourage you to apply if you believe you'd be successful in the role.

You’ll likely bring experience in some of the following areas

  • Developing and deploying machine learning models in production environments.
  • Applying statistical methods to solve real-world problems.

• Experience in one or more of the following areas

  • Time series forecasting
  • Probabilistic forecasting
  • Deep learning
  • Multimodal machine learning
  • Representation learning
  • Causal inference
  • Optimisation
  • Designing new modelling approaches or adapting modern machine learning research to practical business challenges.
  • Proficiency in Python and machine learning frameworks such as Py Torch, Tensor Flow or similar technologies.
  • Experience working with large datasets and distributed data processing environments.
  • Applying software engineering practices including testing, version control and developing maintainable, reproducible code.
  • Collaborating with ML Engineers and cross-functional teams to deploy machine learning solutions into production.
  • Communicating complex scientific concepts clearly to technical and non-technical audiences.
  • Supporting and mentoring colleagues or contributing technical leadership across projects.
  • Curiosity, pragmatism and sound judgement when balancing innovation with business outcomes.
  • Additional Information
  • Bene FITS’
  • Employee discount (hello ASOS discount!)
  • Employee sample sales
  • 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
  • Opportunity for personalised learning and in-the-moment experiences that enable you to thrive and excel in your role
  • #J-18808-Ljbffr

Senior Applied Scientist employer: ASOS.com

As a Digital Trading Assistant at TOPSHOP, you will join a dynamic and innovative team dedicated to redefining fashion retail. With a competitive salary, generous benefits including a performance-related bonus and employee discounts, and a vibrant work culture that encourages creativity and growth, this role offers a unique opportunity to thrive in the heart of London’s fashion scene. The company prioritises employee development and fosters an environment where your contributions directly impact the brand's success, making it an excellent employer for those seeking meaningful and rewarding careers.

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Contact Details:

ASOS.com Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Applied Scientist

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We think you need these skills to ace Senior Applied Scientist

Machine Learning
Statistical Modelling
Deep Learning
Multimodal AI
Time Series Forecasting
Probabilistic Forecasting
Python

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!

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Craft a Tailored Cover Letter:For a full-time role at ASOS.com, 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. 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

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!

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.