The Data Scientist for the AI & Automation Solutions team will provide expert guidance on NLP concepts, assist in technical design reviews, build text corpuses for classification models, leverage all available data for the purposes of training/re-training intents, develop and execute virtual agent performance measurement strategy, and continuously research and prototype the latest data science concepts related to NLP and NLU.

The Data Scientist is responsible for working with the AI & Automation Solution Consultants, Enterprise Architects, IVA Developers, and Conversational Designers to ensure highest levels of accuracy and performance in AI based solutions such as virtual agents, agent guided solutions, and others.

Job Requirements

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 virtual agent 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.

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.

Required Qualifications

· Graduate degree in Statistics, Mathematics, Computer Science, Operations Research, Engineering or similar quantitative field.

· 8+ years’ experience in Python, R, and applied statistics

· 6+ years’ experience with bot frameworks such as IBM Watson, Amazon Lex, and Google Dialogflow

· Experience with Big Data tools such as Elasticsearch, Logstash and Kibana, Apache Kafka, NiFi, Apache Spark, Neo4J, Predictive Insights, and Splunk.

· Experience with Deep Learning Frameworks.

· Experience with interpretability of deep learning models.

· Python experience with ML libraries, such as SciKit Learn, TensorFlow, and Keras on both CPU and GPU compute architectures.

· Hands on experience in working on platforms/environments such as Rasa is a plus

· Hands on experience with GTP3 or GTP-J is a ++

This role is fully remote for candidates who reside at least 50 miles away from our San Francisco or San Ramon office locations. For candidates who reside within 50 miles of our San Francisco or San Ramon locations, this role will be Hybrid.