Applied Scientist - Forecasting

Posted 4 Hours Ago
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London, England, GBR
Hybrid
Mid level
eCommerce • Retail
The Role
Design, develop and productionise machine learning models for large-scale demand forecasting. Improve accuracy, robustness and explainability, run offline/online evaluations, prototype new approaches, and collaborate with engineers and stakeholders.
Summary Generated by Built In
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're looking for an Applied Scientist to join our AI Demand Forecasting team. Our mission is to build forecasting capabilities that support 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 tackling challenging machine learning problems while building reusable forecasting capabilities that can be applied across multiple domains.

As an Applied Scientist, you'll work alongside data engineers, ML engineers, analysts, product managers, and business stakeholders to design, develop and deploy machine learning models at scale. You'll have the opportunity to influence both the scientific direction of our forecasting systems and the products that depend on them.

Key Responsibilities

  • Design, develop and deploy machine learning models for demand forecasting in production environments.
  • Improve forecasting accuracy, robustness, scalability and explainability across diverse business use cases.
  • Develop forecasting solutions that support multiple downstream consumers, including replenishment, pricing and supply chain optimisation.
  • Design and analyse offline and online evaluations to measure model performance and business impact.
  • Collaborate closely with engineers to productionise models and build reliable, scalable ML systems.
  • Explore and evaluate new modelling approaches from industry and academia, testing and prototyping promising ideas.
  • Contribute to the team's scientific direction through technical discussions, code reviews and knowledge sharing.

Qualifications

About You

You'll enjoy applying machine learning to large-scale, real-world forecasting challenges and translating research into production systems.

We'd be particularly interested in candidates who bring experience in some of the following areas:

  • Developing and deploying machine learning models in production environments.
  • Applying statistics, analytics and machine learning techniques to solve real-world problems.
  • Experience in one or more of the following areas:
    • Time series forecasting
    • Probabilistic forecasting
    • Deep learning
    • Gradient boosting
    • Causal inference
    • Optimisation
  • Proficiency in Python and modern machine learning frameworks such as PyTorch, TensorFlow or similar.
  • Working with large datasets and distributed data processing systems.
  • Software engineering practices including testing, version control and writing maintainable code.
  • Communicating technical concepts to both technical and non-technical audiences.
  • Curiosity, pragmatism and a willingness to learn, experiment and share knowledge.

Additional Information

BeneFITS’ 

  • 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 
  • Fixed Annual Payment in addition to your salary each year, it's just an extra thank you from us 
  • Opportunity for personalised learning and in-the-moment experiences that enable you to thrive and excel in your role 

Skills Required

  • Developing and deploying machine learning models in production environments.
  • Applying statistics, analytics and machine learning techniques to real-world problems.
  • Experience with time series forecasting.
  • Experience with probabilistic forecasting.
  • Experience with deep learning.
  • Experience with gradient boosting.
  • Experience with causal inference.
  • Experience with optimisation.
  • Proficiency in Python.
  • Proficiency with modern ML frameworks such as PyTorch or TensorFlow.
  • Working with large datasets and distributed data processing systems.
  • Software engineering practices including testing, version control and writing maintainable code.
  • Communicating technical concepts to both technical and non-technical audiences.
  • Curiosity, pragmatism and a willingness to learn, experiment and share knowledge.

ASOS Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about ASOS and has not been reviewed or approved by ASOS.

  • Wellbeing & Lifestyle Benefits Feedback suggests perks like a sizable, shareable product discount, access to sample sales, free gym access, and on-site amenities are valued. Such lifestyle-oriented benefits are frequently highlighted as standout aspects of the package.
  • Leave & Time Off Breadth Feedback suggests employees benefit from substantial annual leave with bank holidays and an extra celebratory or birthday day off, with summer early finishes referenced in some contexts. This breadth of time-off options supports work-life balance.
  • Healthcare Strength Feedback suggests access to a private medical care scheme is a core part of the package. This contributes to a perception of strong healthcare support.

ASOS Insights

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The Company
HQ: London
3,200 Employees
Year Founded: 2000

What We Do

We exist to give people 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 judgment, and channel your creativity into a platform used by millions. Whatever your role, asos will encourage you to be you, fulfilling your creative potential with our global reach. Push boundaries, and challenge expectations. We’re determined to succeed, so we’ll trust you to deliver. Help drive our journey to becoming the global fashion destination for 20-somethings At ASOS our 3,000+ employees are immersed in the creative worlds and have a truly entrepreneurial attitude. Our ASOSers are authentic, brave, creative and disciplined to the core and find ways to blend our passion for fashion with cutting edge technology. Sound up your street? Join us.

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