Significant prior experience with applying Big Data tools (MapReduce, Hadoop, Hive and / or Pig, Spark) to large quantities of textual data.
Strong communication and presentation skills, can concisely and accurately convey experimental results and interpretations.
Experience with non- English NLP Models.
Proven ability to lead technical projects and set & achieve realistic deadlines.
Expertise in Python programming, with hands- on experience in one of the web frameworks like Django, Flask, Tornado, etc.
Expert knowledge of algorithms and data structures.
Familiarity with some ORM (Object Relational Mapper) libraries.
Able to integrate multiple data sources and databases into one system.
Understanding of the threading limitations of Python, and multi- process architecture.
Understanding of fundamental design principles behind a scalable application
Experience with machine learning frameworks (like Tensorflow, Keras or PyTorch) and libraries (like scikit- learn).
Experience with classification, feature engineering, information extraction, structured prediction, clustering, semi- supervised learning, topic modeling, and ranking.
Statistical analysis of results and refine models.
Proficient in Python with sound knowledge in the data science libraries namely Numpy, Pandas, Gensim / SpaCy / NLTK etc.
Experience in projects relevant to Sentiment Analysis, Entity Extraction, Document Classification, Semantic analysis, Topic Modeling and Natural Language Generation (NLG).
Understanding of text pre- processing and normalization techniques, such as tokenization, POS tagging and parsing.
Expertise in processing, evaluating and utilizing training, testing and validation data.
Experience with noisy and / or unstructured textual data (e.g. tweets).
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