Machine Learning Data Scientist - NLP

• Deep understanding of machine learning (ML) deep learning algorithms.
• Expertise in developing natural language processing (NLP)/understanding algorithms/models required.
• Expertise applying deep learning techniques to NLP/U problems required, including thorough knowledge of the theory and practice of NLP and deep-learning techniques.
• Knowledge of most of the following quantitative fields: NLP, information retrieval, machine comprehension, question answering/conversational AI, reinforcement learning, knowledge graph, causal inference, and design of experiment.
• Statistical and data science programming skills, such as Python and R.
• Experience in big data, search, NLP, and chatbot technologies such as Elasticsearch and Solr.
• Strong coder with experience building models and analyzing data using machine learning (ML), knowledge of deep learning and related tools such as TensorFlow, Keras, MXNET, and other open source and third-party products like H2O is essential.
• Well-versed with open source and other algorithms RASA, GPT, Hugging Face, etc.
• Knowledge of advancements in AI, deep tech, and ability to apply quickly.
• Strong experience implementing models in production.
• Ability to craft new concepts and stay current with academic research. Published research is a plus.
• Strong experience working with non-technical stakeholders.
• Ability to summarize research and analysis for audiences with varying levels of expertise.
• Experience deploying NLP solutions in a commercial environment.

Any graduate / postgraduate with a degree in Computer Science, Statistics, Analytics, Data Science/ Information Systems, or another quantitative field.