Senior Data Scientist

Responsibilities:

• Design, develop, and deploy advanced ML models for supply chain demand forecasting, inventory optimisation, and operational efficiency.
• Develop predictive models and optimisation algorithms using Python and ML frameworks.
• Build scalable, production-ready ML pipelines with automated testing and deployment.
• Collaborate with Data Platform, Product, and Engineering teams for model integration.
• Perform feature engineering, model training, performance tuning, and monitoring.
• Maintain code quality and stay updated with advancements in ML and Deep Learning.

Requirements:

• 3+ years of industry experience with a Bachelor's degree or 2+ years with a Master's degree in Computer Science, Mathematics, Statistics, or a related field.
• 2+ years of hands-on experience in Machine Learning / Data Science.
• Experience in Supply Chain Forecasting, Time-Series Modelling, or Operations Optimisation.
• Strong proficiency in Python and ML libraries such as Scikit-learn, PyTorch, TensorFlow, or Keras.
• Experience deploying ML models into production.
• Strong understanding of statistical modelling, ML algorithms, and scalable systems.

Nice to Have:

• Experience with demand forecasting, inventory optimisation, or logistics analytics.
• Knowledge of Spark, PySpark, SQL, and distributed computing.
• Experience with cloud platforms (AWS, GCP, Azure).
• Familiarity with MLOps tools such as MLflow, Airflow, or Kubeflow.
• Experience with optimisation tools such as Gurobi, OR-Tools, or Pyomo.
• Required Skills: Python, Machine Learning, Supply Chain Forecasting, Time-Series Forecasting, Operations Optimisation, PySpark, Deep Learning, Statistical Modelling, SQL, MLOps.

Skills

Data Science, Forecasting, ML, Machine Learning, Optimization, Python, Time-Series