Jubil ID: 35

Company: Diverse Lynx

Location: Princeton, NJ

Description:
Salary:About Us:CXAPP is a forward-thinking technology company that leverages AI and data science to drive innovation and deliver cutting-edge solutions. We are seeking talented AI Applications and Data Science Engineers with expertise in NLP, chatbots, predictive analytics, recommendation systems, data engineering, and automation to join our dynamic team.Job Description:As an AI Application

Qualifications:
Masters degree in computer science
Data Science
or a related field Expertise in NLP techniques like tokenization
stemming
lemmatization
and sentiment analysis is required for processing and understanding natural language dialogue Knowledge of dialogue state tracking
act classification
and context management is essential for maintaining coherent and engaging conversation flows Strong expertise in predictive analytics and recommendation systems Proficiency in data engineering
ETL processes
and data automation Hands-on experience with AI and data science tools and frameworks Programming skills in Python
Java
or relevant languages Knowledge of cloud platforms

Benefits:
Competitive salary and performance-based bonuses Comprehensive health
dental
and retirement plans Opportunities for professional development and growth A dynamic and collaborative work environment The chance to work on cutting-edge AI projects with a talented team

Responsibilities:
You will play a pivotal role in designing and developing AI-driven applications and systems
including NLP-powered chatbots
predictive analytics models
recommendation engines
and data automation solutions This role offers a unique opportunity to work on exciting projects and make a meaningful impact on our organization and clients NLP and Chatbot Development: Lead the design
development
and maintenance of NLP-powered chatbots and virtual assistants to enhance user experiences and automate interactions Predictive Analytics: Design and implement predictive models to forecast trends
user behavior
and business outcomes
providing data-driven insights Recommendation Systems: Develop recommendation engines that personalize content
products
or services for users
optimizing engagement and satisfaction Data Engineering: Build robust data pipelines
data lakes
and ETL processes to collect
preprocess
and transform data for analysis and modeling Automation: Implement automation solutions for repetitive tasks
optimizing efficiency and reducing manual workloads AI Integration: Collaborate with cross-functional teams to integrate AI and data science capabilities into existing systems and applications Performance Optimization: Optimize the performance and scalability of AI applications
ensuring real-time responsiveness Data Security and Compliance: Implement data security measures and ensure compliance with relevant data privacy regulations