Data Scientist

We are seeking a Data Scientist to improve and evolve forecasting models within the Fulfilment Forecasting and Planning area of the Fulfilment and Core Services domain. This cross-functional area builds digital products, including the Retail Planning Platform (RPP), an in-house planning platform providing demand forecasts and planning decision support for global supply chain logistics. These products are used globally and developed by teams of product owners, data scientists, software engineers, and business partners., The consultant will focus on developing, improving, and maintaining data science, machine learning, and data engineering models, particularly for Sales and Services Forecasting. This involves exploring logistics planning processes within the supply chain and collaborating with diverse stakeholders to identify key factors impacting operations.

• Experience in forecasting problems, especially in logistics and supply chain.
• Strong scientific background, curiosity about business domains, and proactive communication skills.
• Ability to write production-ready Python code, review PRs, and maintain extendable codebases.
• Experience with ML libraries/frameworks (XGBoost, scikit-learn, TensorFlow, PyTorch).
• Strong knowledge of Google Cloud Platform (GCP), including Cloud Storage and BigQuery.
• Familiarity with MLOps tools (Metaflow, BentoML, KubeFlow).
• Ability to understand and debug code.
• Apply analytical findings to real-world business problems.
• Excellent problem-solving skills and strategic mindset.
• Ideally, knowledge of IaC tools (Terraform), automated testing, and CI/CD tools (GitHub Actions).
• Ability to work in cross-functional teams and demonstrate good business acumen.

Top 3 Priorities:

1. Experience in forecasting problems, especially in logistics and supply chain.
2. Affinity with software engineering practices in the data science space.
3. Cross-functional collaboration and strong business acumen.