Requirements:

The ideal candidate should have:

Experience in forecasting problems and affinity with logistics and supply chain domain.

Strong scientific background, business domain curiosity and proactive communication skills.

Ability to write production-ready Python code, review PRs, and contribute to maintainable, usable, and extendable codebases.

Experience with Machine Learning libraries and frameworks (e.g., XGBoost, scikit-learn, TensorFlow, PyTorch).

Strong knowledge of cloud services, especially Google Cloud Platform (GCP), including Cloud Storage or BigQuery.

Familiarity with open-source MLOps tools like Metaflow, BentoML, KubeFlow, or similar.

Confidence in digging into code and understanding how things are working.

Demonstrated ability to apply analytical findings to real-world business problems.

Excellent problem-solving skills with a strategic mindset.

Ideally, knowledge of Infrastructure as Code (IaC) tools like Terraform, automated testing and CI/CD tools like GitHub Actions.

Ability to work in cross-functional teams with product owners, data scientists, backend engineers, and frontend engineers.

Good business acumen