NLP Data Scientist - Cuddle.ai

Job Description

NLP Data Scientist:About Fractal :Fractal is one of the most prominent players in the Artificial Intelligence space. Fractal s mission is to power every human decision in the enterprise and uses the power of AI to help the world s most admired Fortune 500 companies. Fractal s products include Qure.ai to assist radiologists make better diagnostic decisions, Cuddle.ai to assists CEOs and senior executives make better tactical and strategic decisions, Theremin.ai to improve investment decisions and Eugenie.ai to find anomalies in high velocity data. Fractal has consistently been rated as India s best companies to work for, by The Great Place to Work Institute. Fractal has been featured as a leader in the Customer Analytics Service Providers Wave 2019 by Forrester Research, and recognized as an Honorable Vendor in 2019 magic quadrant for data & analytics by Gartner.About Cuddle.aiCuddle is an AI-powered voice-enabled business analysis platform used by multiple Fortune 500 companies. Cuddle brings the simplicity of Siri at work - alerting users on what they need to know before they ask & answering data questions in natural language on mobile. Incubated by Fractal, Cuddles team comprises of Engineers, data-scientists & product designers based in US and India. To know more, visit http://www.cuddle.aiPersonality Traits

• Ability to work independently under tight deadlines with accountability.
• Strong results driven personality with a high level of enthusiasm, energy and confidence.
• Strong problem-solving skills.

Required Skills

• In-depth knowledge of various Natural Language Processing/Understanding (NLP/NLU) domains such as entity extraction, speech recognition, topic modeling, parsing, question answering, etc.
• Expertise in text mining (probabilistic topic model, word association mining, ontology learning, semantic similarity, etc.)
• Expertise in NLP/NLU (word representation, relation extraction, natural language inference, semantic parsing, etc.)
• Excellent background in Machine Learning (generative model, discriminative model, neural network, regression, classification, clustering, etc.)
• Experience in deep learning on NLP/NLU is a big plus
• Extensive experiences in using NLP related techniques/algorithms such as HMM, CRF, deep learning & recurrent ANN, word2vec/doc2vec, Bayesian modeling, etc.
• Experience in applied statistics including sampling approaches, modeling, and data mining techniques
• Experience in building analytical models and working with structured and unstructured data
• Experience with data structures and algorithms; ability to work in a Unix environment and building robust data processing and analytics pipelines
• Contributions to research communities, e.g. ACL, NIPS, ICML, EMNLP, etc. is a Plus

Responsibilities:

• You will be part of a high impact team that s building the next generation of intelligence and language understanding for Cuddle
• Build text/voice-based search engine and question answering system for Cuddle
• Youll utilize the latest techniques in AI, ML (including Deep Learning approaches) and NLU
• Build topic analysis, text classification, named entity recognition methods for unstructured and semi-structured data
• Develop and perform text classification using methods such as logistic regression, decision trees, SVM and maximum entropy classifiers
• Perform text mining, generate and test working hypotheses, prepare and analyze historical data and identify patterns
• Generate creative solutions (patents) and publish research results in top conferences (papers)

Qualifications

• /Masters degree in Mathematics, Statistics, Computer Science, or related fields
• 2+ years of ML + NLP experience
• Software programming in Java or Python
• Knowledge of SQL and NoSQL databases
• Knowledge of open source machine learning libraries like scikit-learn, tensorflow, NLP tool as NLTK

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Keyskills :
analyticsopen sourcedata processingdata analysisdecision treessqlproblem solvingsearch enginetext miningfortune 500pythondeep learningdata structuresdata miningmachine learning