Data Scientist

About the role

As a Data Scientist you will join a global, high‑performing team to design, build and operationalise advanced data science and machine‑learning solutions. Your work will directly support customer experience, demand forecasting, operations optimisation and revenue growth across B2B and digital‑commerce environments.

Key responsibilities

• Design, develop and deploy predictive and prescriptive models for customer experience optimisation, demand forecasting, operations efficiency and behaviour analysis.
• Apply machine‑learning techniques such as Gradient Boosting, Random Forests, SVMs, LSTM and Transformers to solve complex business problems.
• Build and maintain recommendation systems, churn prediction, propensity modelling, segmentation, matching and assortment optimisation models.
• Perform feature engineering, clustering, statistical modelling and time‑series analysis on structured and unstructured data.
• Transition models from notebooks to production‑ready artifacts, including APIs, serialized models and containerised solutions.
• Collaborate with engineering to implement MLOps pipelines, CI/CD, model versioning, automated deployment, monitoring and retraining.
• Conduct advanced statistical analysis, A/B testing and causal inference to deliver actionable insights.
• Partner with product, engineering, analytics and business stakeholders to prioritise data‑science opportunities.

Required profile

• 3+ years of hands‑on experience in applied data science and machine learning, preferably in B2B, retail or digital‑commerce.
• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Analytics or a related field.
• Strong proficiency in Python and its data‑science ecosystem.

Required skills

• Python
• Pandas
• NumPy
• Scikit‑learn
• Gradient Boosting
• Random Forests
• Support Vector Machines (SVM)
• LSTM
• Transformers
• API development
• Containerisation (e.g., Docker)
• CI/CD pipelines
• MLOps practices