Python programming (NumPy, Pandas, Scikit-learn)

Machine Learning algorithms and frameworks (TensorFlow, PyTorch, XGBoost, LightGBM)

Statistical analysis and hypothesis testing

Time series forecasting and ARIMA/Prophet models

Optimization algorithms and linear/integer programming

SQL and database management

Data visualization tools (Matplotlib, Seaborn, Tableau, Power BI)

Big data technologies (Spark, Hadoop)

Model deployment and MLOps (Docker, Kubernetes, CI/CD pipelines)

Computer Vision libraries (OpenCV, PIL) - if applicable

NLP libraries (NLTK, spaCy, Transformers) - if applicable

Git and version control systems

Cloud platforms (AWS SageMaker, GCP Vertex AI, Azure ML) - preferred

Strong problem-solving and analytical thinking abilities

Excellent communication skills with ability to explain complex ML concepts to non-technical stakeholders

Leadership and mentoring capabilities

Collaboration and teamwork across cross-functional teams

Project management and ability to prioritize multiple initiatives

Business acumen and understanding of supply chain/operational challenges

Attention to detail and commitment to code quality

Curiosity and passion for continuous learning

Ability to work independently and take ownership of projects

Presentation skills for stakeholder communication