Data Scientist / Conversational AI

Compunnel Inc.

San Francisco, CA, USA

Full-time

Conversation Design

Sep 9

Description-

Primary Skills: NLP, Chatbot Search/Conversational AI, Python, SQL


Utilize NLP to build chatbot that will be utilized by Schwab clients and prospects across different channels and instrument Dialogflow for intents

Get hands-on with large disparate datasets, hack through complex and messy data, and analyze it leveraging the latest algorithms and state-of-the-art techniques and tools.

Use open source tools and platforms like Anaconda Enterprise, Python and R to apply algorithms and analytic models to big data problems.


NLP:

Knowledge of NLP concepts and hands on experience in building Text classification ML/statistical model and implementing entity extraction algorithms.

Ability to make data driven decisions to train and re-train Dialogflow intents.

Experience with extracting relevant data from user transcripts including cleaning, lemmatizing and building text corpus for building classification models

Machine Learning: Knowledge of and experience with designing and implementing algorithms (clustering, decision tree learning, GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc), and the ability to articulate their real-world advantages and drawbacks.


Knowledge Graph: Experience working with knowledge graphs in chatbots or Search.

Statistical Methodology: Knowledge of advanced techniques and concepts (sampling, A/B testing, regression, properties of distributions, statistical tests and proper usage, etc).

Ability to understand model performance

Business acumen: You understand the bigger picture for customers and the business and know how to probe beyond stakeholders’ stated requests to really understand their needs and the value of information.

 




Education: Bachelors Degree


Additional client information:

Please note that the end client name may not be displayed due to confidentiality agreements. The client’s name will be disclosed by the recruiter prior to submission.


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