Data Scientist

Requirements:

• Strong proficiency in Python.
• Hands-on experience delivering end-to-end NLP projects. (NER/spacy/feature eng).
• Solid understanding of machine learning, deep learning, and transformer-based architectures.
• Practical experience implementing and deploying models such as LSTM, BERT, or similar architectures in production or real-world applications.
• Hands-on experience with ML frameworks such as PyTorch, TensorFlow, or JAX.
• Fine-tuning models.
• Good with metrics.
• Strong understanding of modern ML techniques, including Deep Neural Networks (DNNs), multi-task learning, and transformer architectures.
• Good knowledge of mathematical optimization techniques, such as multi-objective optimization, linear programming (LP), and convex optimization.