Netomi is a Y-Combinator and VC-backed Artificial Intelligence company that sits at the intersection of two rapidly developing fields: AI and customer service.
Our clients include Fortune 1,000 companies. Our artificial intelligence platform gives customer service teams the ability to activate, manage & train their AI to deliver an experience that delights consumers and turns customer service into a competitive advantage.We care about building a company that not only has the best technology and product on the market but also provides superior service to our customers.Want to have a direct impact on solving the top challenges businesses face today? Join us!Job Description:- Do you believe in the mission Intelligence agencies? Are you interested in solving complex programmatic and technical issues?If you are interested in working on some of the most challenging technical and programmatic issues, we are interested in talking to you about Netomi's work and career opportunities.As a Data Scientist at Netomi, you will drive NLP and machine learning projects and be responsible for developing methodology and solutions to support technical, analytical, and operational requirements.Job Responsibilities: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 advisors to define the roadmap of the project Requirements:- Bachelors/Masters or higher degree in Computer Science or related technical field- 1-2 years of work experience related to classifications, clustering, Knowledge representation, Information Extraction, and Reasoning.- 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, support vector machines (SVM) neural networks, Random Forest, CRF, Bayesian models, supervised/unsupervised learning, etc. - The ideal candidate will have wide coverage of the different methods/models, and 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 Open NLP, Mallet, Ling pipe, NLTK).- Deep knowledge and experience in both key areas Information Extraction (from structured and unstructured data and represent that knowledge) Knowledge Information Retrieval.- It would be good to have if the candidate has knowledge of Deep Learning(ANN, CNN, RBM)