Python programming (NumPy, Pandas, Scikit-learn)

Deep Learning frameworks (TensorFlow, PyTorch, Keras)

Machine Learning algorithms (supervised, unsupervised, reinforcement learning)

Data preprocessing and feature engineering

SQL and database management

Data visualization tools (Matplotlib, Seaborn, Plotly)

Version control (Git)

Model deployment and serving (Flask, FastAPI, Docker)

Cloud platforms (AWS SageMaker, Google Cloud AI, Azure ML)

MLOps tools and practices (CI/CD, model monitoring)

Big Data technologies (Spark, Hadoop) - preferred

API development and integration

Strong problem-solving and analytical thinking abilities

Excellent communication and presentation skills

Ability to work collaboratively in cross-functional teams

Self-motivated with strong attention to detail

Ability to translate business requirements into technical solutions

Continuous learning mindset and adaptability

Project management and time management skills

Critical thinking and decision-making abilities

Mentoring and knowledge-sharing capabilities