● Strong programming skills in Python and familiarity with
ML/data science libraries (pandas, NumPy, scikit-learn,
PyTorch/TensorFlow).
● Hands-on experience or coursework involving data cleaning,
preprocessing, feature extraction, and EDA.
● Understanding of machine learning algorithms, supervised and
unsupervised methods.
● Basic knowledge or interest in AI privacy techniques and edge
computing is a plus.
● Ability to work independently on data-driven problems and
collaborate remotely.
● Good communication skills to articulate findings and collaborate
effectively.
● Experience with cloud platforms, databases, or data versioning
tools.
● Familiarity with containerization, MLOps pipelines, or workflow
automation frameworks.
● Participation in data science competitions, projects, or open-
source contributions.
● Background in computer science, data science, AI, or related
fields from reputed institutions.