Data Scientist

Description:

They’re now looking to bring on a Data Scientist to join their Forecasting Algorithms team. You'll work on highly granular demand forecasting models that operate at scale and in production, influencing customer outcomes and product decisions. This is a great opportunity to deepen your experience in time series modelling and production ML within a collaborative, technically rigorous environment.

Key Responsibilities

• Design, develop, and maintain forecasting models using time series and deep learning techniques
• Build and iterate on internal ML libraries and tools to improve model performance and reliability
• Collaborate with product and data science leads to translate business problems into modelling solutions
• Implement clean, production-grade code and contribute to testing, monitoring, and validation pipelines
• Explore and apply new modelling techniques from across the ML/AI ecosystem
• Communicate findings clearly to technical and non-technical stakeholders

About You

You’re a hands-on data scientist with a strong interest in forecasting, time series analysis, and production machine learning. You enjoy digging into the details of modelling techniques, writing reliable code, and working collaboratively with others to solve real-world problems at scale.

Requirements:

• 2–4 years of experience in a data science or applied machine learning role
• Strong Python skills with experience in libraries like NumPy, Pandas, Scikit-learn, SciPy
• Experience with time series modelling and/or demand forecasting
• Familiarity with cloud tools (e.g. GCP, AWS) and orchestration frameworks (e.g. Dagster, Airflow)
• Good understanding of model validation, metrics, and reproducibility
• Comfortable writing clean, tested, and maintainable code
• Exposure to deep learning architectures (e.g. CNNs, transformers) is a plus but not essential