Education: Advanced Degree in a quantitative discipline such as Computer Science, Engineering, Econometrics, Statistics or Information Sciences such as business analytics or informatics    

Required Skills: 

• Familiarity with the Conversational AI domain, conversational design & implementation, customer experience metrics, and industry-specific challenges.   

• Understanding of conversational (chats, emails and calls) data and its preprocessing (including feature engineering if required) to train Conversational AI systems. 

• Strong problem-solving and analytical skills to troubleshoot and optimize conversational AI systems 

• Familiarity with NLP/NLG techniques such as parts of speech tagging, lemmatization, canonicalization, Word2vec, sentiment analysis, topic modeling, and text classification 

• NLP and NLU Verticals Expertise: Text to Speech (TTS), Speech to Text (STT), SSML modeling, Intent Analytics, Proactive Outreach Orchestration, OmniChannel AI & IVR (incl. Testing), Intelligent Agent Assist, Contact Center as a Service (CCaaS), Modern Data for Conversational AI and Generative AI. 

• Experience building chatbots using bot frameworks like RASA/ LUIS/ DialogFlow/Lex etc and building NLU model pipeline using feature extraction, entity extraction, intent classification etc.  

• Understanding of cloud platforms (e.g., AWS, Azure, Google Cloud, Omilia Cloud Platform, Kore.ai, OneReach.ai, NICE, Salesforce, etc.) and their services for building Conversational AI solutions for cliients 

• Expertise in Python or PySpark. R and JavaScript framework. 

• Expertise in visualization tools such as Power BI, Tableau, Qlikview, Spotfire etc. 

• Experience with evaluating and improving conversational AI system performance through metrics and user feedback. 

• Excellent communication skills. 

• Familiarity with Agile development methodologies and version control systems. 

• Ability to stay updated with the latest advancements and trends in conversational AI technologies. 

• Strong attention to detail and ability to deliver high-quality work within deadlines. 

Nice to Have:   

• Familiarity with data wrangling tools such as Alteryx, Excel and Relational storage (SQL) 

• ML modeling skills: Experience in various statistical techniques such as Regression, Time Series Forecasting, Classification, XGB, Clustering, Neural Networks, Simulation Modelling, Etc. 

• Experience in survey analytics, organizational functions such as pricing, sales, marketing, operations, customer insights, etc. 

• Understanding of NoSQL databases (e.g., MongoDB, Cassandra) for handling unstructured and semi-structured data.