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ASOS • London, United Kingdom

Applied Scientist - Forecasting

Employment type:  Full time
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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'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
Apply now

Company benefits

25 days annual leave + bank holidays
401K
Accrued annual leave – Max 5 days to carry over
Adoption leave – 26 weeks enhanced pay
Annual bonus
Annual pay rises
Bike parking
Birthday off
Buy or sell annual leave
Cinema discounts
Coffee discounts
Company freebies
Compassionate leave
Critical Illness Insurance
Dental coverage
Early finish Fridays
Emergency leave
Employee assistance programme
Employee discounts
Enhanced maternity leave – 26 weeks enhanced pay
Enhanced paternity leave – 8 weeks enhanced pay
Enhanced pension match/contribution
Enhanced sick days
Enhanced sick pay
Eye Care Support
Faith rooms
Family health insurance
Fertility benefits
Financial coaching
Further education support
Gym membership
Hackathons
Health insurance
Hertility subscription
In house training
On-site catering
On-site massages
On-site workout classes
On-site yoga classes
Learning platform
Life assurance
Mental health first aiders
Mental health platform access – Access to EAP (Unum)
Mentoring
Neonatal leave – 16 weeks leave
On-site gym
On-site wellness room
Open to compressed hours
Open to part time work for some roles
Open to part-time employees
Personal development days
Pregnancy loss leave – 10 days paid leave
Private GP service
Professional subscriptions
Referral bonus
Religious celebration leave
Restaurant discounts
Sabbaticals
Salary sacrifice
Shared parental leave – 26 weeks enhanced pay
Skilled worker visas
Study support
Teambuilding days
Time off in-lieu
Travel loan
Volunteer days
Summer hours
Secure on-site parking
Modern office
Private booths
Collaboration spaces
On-site barista
On-site shower
On-site personal trainer
Carer’s leave
Fertility treatment leave
Women’s health leave
Menopause support

Working at ASOS

Company employees:

3,000

Gender diversity (m:f):

35:65

Hiring in countries

Türkiye

United Kingdom

Office Locations

Awards & Accreditations

2nd – Most loved - Medium companies

2nd – Most loved - Medium companies

Flexa awards 2026

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