Data Scientist

Responsibilities:

• Design, build and optimise time series forecasting models for demand prediction at fine-grained levels of granularity
• Develop a many-models approach that supports large numbers of individual keys at the lowest level of aggregation
• Implement a logical model selection layer that segments time series based on statistical and behavioural characteristics
• Select, train, retrain and deploy appropriate forecasting models per segment, adapting to changing data patterns
• Build and operationalise pipelines in Azure ML Studio for training, evaluation and deployment
• Collaborate closely with other data scientists to agree modelling standards, evaluation metrics and architectural patterns
• Work with stakeholders to translate business requirements into robust forecasting solutions
• Ensure solutions are production-ready, scalable and maintainable

Requirements:

• Strong experience in time series forecasting, including classical and machine learning based approaches
• Proven experience building multi-model or many-model forecasting solutions
• Solid understanding of time series diagnostics, segmentation and model selection techniques
• Hands-on experience with Azure, particularly Azure ML Studio and related MLOps tooling
• Strong Python skills and experience with common data science and time series libraries
• Experience working in collaborative data science teams on commercial forecasting problems
• Fluent English

Nice to have:

• Experience with hierarchical or bottom-up demand forecasting
• Familiarity with automated retraining strategies and model monitoring
• Experience deploying forecasting solutions into production environments
• Understanding of retail, supply chain or commercial demand forecasting use cases

Offer:

• Constant support of dedicated consultant
• Employee referral program