Job Description
● Build algorithms and data structures for fast and real-time data processing.
● Build and implement required algorithms for practical use of tests' output.
● Convert data to knowledge and change algorithms in cooperation with other teams.
● Work with basic NlP techniques such as vectorizing, text clustering, word embeddings, and QA.
● Implement basic machine learning techniques and algorithms such as supervised and unsupervised learning techniques, recommendation algorithms, predictive modeling, and statistics.
● Implement modern deep learning architectures for NLP. (encoder-decoder, transformers, attention).
● Work with software and programs in Python data science ecosystems such as Pandas, NumPy, SciPy, Sci-Kit-Learn, NLTK, Gensim, etc.
● Evaluate the quality of ML models to define the right performance metrics in accordance with the requirements of core platform.
● Use the code versioning tools such as Git.
