Job Description
- Apply knowledge in one or more of the following areas to achieve goals and deliver results
- NLP and Machine learning
- Computer programming (programming languages, computer science, scientific computing)
- Computer analytics architecture (e.g. distributed computing and modern databases)
- Works collaboratively in a multi-disciplinary team environment; establishes and maintains professional networks with subject matter experts.
- Work as a direct contributor and key technical advisor to define the roadmap of projects
- Bachelor’s or Master’s degree in Applied Mathematics, Statistics, Computer Science or another quantitative field.
- 1+ years of work experience related to statistical analysis, machine learning models and programming.
- Self-motivated and driven to satisfy intellectual curiosity through the pursuit of learning and development of new skills.
- Experience working with a wide variety of statistical models such as linear/logistic regression, clustering, classification, support vector machines (SVM) neural networks, Random Forest, CRF, Bayesian models, supervised/unsupervised learning, etc. The ideal candidate will have a wide coverage of the different methods/models, and an in-depth knowledge of some.
- Knowledge of Natural Language Processing (NLP) techniques (POS Tagging, NER, Semantic Role Labelling etc.) and good working experience with at least one of the frameworks (e.g. Stanford NLP, Apache OpenNLP, Mallet, Ling pipe, NLTK).
- Deep knowledge and experience in Information Extraction ( structured and unstructured data), Knowledge Information Retrieval and Knowledge Representation.
- It would be good to have if the candidate has knowledge of Deep Learning (ANN, CNN, RBM) and has NLP Deep Learning experience related to Word2Vec, Thought Vectors.
Date Posted
11/16/2023
Views
6
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