Data Scientist

Dünən

301

Experience in statistical and machine learning models;
Strong understanding of prompt engineering and in-context learning;
Experience in building and evaluating language models for domain-specific applications;
Hands-on experience in RAG pipeline development, indexing strategies, and integrating vector databases for NLP tasks;
Understanding of FAISS, Pinecone, Weaviate, and other vector search databases;
Work with large-scale datasets, ensuring efficiency in training and inference;
Stay updated with the latest research in NLP and propose innovative solutions.

1+ years of professional experience in data science, with a strong foundation in machine learning and statistical modeling.
Proven ability to develop and fine-tune transformer-based models, with a focus on low-resource languages, particularly Azerbaijani.
Solid expertise in Python programming, including libraries such as NumPy, pandas, scikit-learn, PyTorch, and Hugging Face Transformers.
Deep understanding of the data science lifecycle—from data preprocessing and feature engineering to model training, evaluation, and deployment.