Applied Scientist Forecasting

Were 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 were 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 youll work alongside data engineers ML engineers analysts product managers and business stakeholders to design develop and deploy machine learning models at scale. Youll 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 teams scientific direction through technical discussions code reviews and knowledge sharing.

Qualifications :

About You

Youll enjoy applying machine learning to large-scale real-world forecasting challenges and translating research into production systems.

Wed 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 its 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 

Remote Work :

No

Employment Type :

Full-time