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Conversational Ai Analyst Jobs (NOW HIRING)

Saransh Inc

Conversational AI Developer

Irving, TX · On-site

Conversational AI Developer Locations: Irving/Dallas, Texas & Jacksonville Florida Duration ... sentiment analysis to understand user queries effectively. * Ensure security and compliance:

OVA.Work

Conversational AI Developer

... analytics, user feedback, and AI evaluation metrics. • Implement guardrails, content moderation, authentication, and security best practices for conversational AI applications. • Collaborate with ...

Worky

Conversational AI Engineer

San Diego, CA · On-site

$70 - $93/hr

Responsibilities: Conversational AI Platform Development: * Design, build, and support ... Perform root-cause analysis for defects, outages, and performance issues, and implement long-term ...

New

Forhyre

Product Manager - Conversational AI

Phoenix, AZ · On-site

Conduct market research and analysis to identify customer needs, trends, and opportunities in the Conversational AI space. * Collaborate with cross-functional teams including engineering, design, and ...

Forhyre

OH · On-site

Conduct market research and analysis to identify customer needs, trends, and opportunities in the Conversational AI space. * Collaborate with cross-functional teams including engineering, design, and ...

Forhyre

Product Manager - Conversational AI

Plano, TX · On-site

Conduct market research and analysis to identify customer needs, trends, and opportunities in the Conversational AI space. * Collaborate with cross-functional teams including engineering, design, and ...

Forhyre

Conduct market research and analysis to identify customer needs, trends, and opportunities in the Conversational AI space. * Collaborate with cross-functional teams including engineering, design, and ...

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Conversational Ai Analyst information

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How much do conversational ai analyst jobs pay per hour?

As of Aug 29, 2026, the average hourly pay for conversational ai analyst in the United States is $35.97, according to ZipRecruiter salary data. Most workers in this role earn between $25.24 and $42.07 per hour, depending on experience, location, and employer.

What does a conversational AI analyst do?

A Conversational AI Analyst is responsible for designing, analyzing, and optimizing AI-driven conversational interfaces such as chatbots and virtual assistants. They use data to evaluate user interactions, identify patterns, and suggest improvements to enhance user experience and accuracy. Their work often involves collaborating with developers, data scientists, and UX designers, as well as conducting A/B testing and monitoring performance metrics. The ultimate goal is to ensure the conversational AI systems are effective, efficient, and aligned with business objectives.

What are the key skills and qualifications needed to thrive as a conversational AI analyst?

To thrive as a Conversational AI Analyst, you need a solid background in data analysis, natural language processing (NLP), and linguistics, often supported by a degree in computer science, linguistics, or a related field. Familiarity with analytics platforms, chatbot development tools (such as Dialogflow or Rasa), and scripting languages like Python is typically required. Strong problem-solving ability, attention to detail, and effective communication skills help you interpret data insights and collaborate with cross-functional teams. These competencies are crucial for designing, optimizing, and evaluating AI-driven conversational systems to ensure accurate and user-friendly interactions.

What are some common challenges faced by conversational AI analysts when improving chatbot performance?

Conversational AI Analysts often encounter challenges such as accurately interpreting user intent, handling ambiguous queries, and managing the evolving language used by customers. They must continuously analyze conversation logs, identify areas where the AI fails to provide satisfactory responses, and collaborate with data scientists, developers, and UX designers to refine natural language models. Staying up-to-date with advancements in NLP technologies and ensuring that the chatbot aligns with business goals are also important aspects of the role.

What is the difference between Conversational Ai Analyst vs Data Analyst?

AspectConversational Ai AnalystData Analyst
Required CredentialsBachelor's in CS, Data Science, or related; knowledge of NLP and AI toolsBachelor's in Statistics, Math, or related; proficiency in data analysis tools
Work EnvironmentTech companies, AI startups, customer service platformsBusiness, finance, healthcare, and other industries
Employer & Industry UsageAI-focused companies, tech firms, customer experience teamsVarious sectors analyzing data for insights and decision-making

The Conversational Ai Analyst specializes in developing and optimizing AI chatbots and voice assistants, focusing on natural language processing. In contrast, the Data Analyst interprets data sets to inform business decisions across industries. While both roles require analytical skills and familiarity with data tools, the Conversational Ai Analyst emphasizes AI and NLP technologies, whereas the Data Analyst centers on data visualization and statistical analysis.

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Conversational Ai Analyst jobs near you
Infographic showing various Conversational Ai Analyst job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 21% Part Time, and 3% Contract. Highlights an 64% Physical, 4% Hybrid, and 32% Remote job distribution, with an average salary of $74,823 per year, or $36 per hour.

Conversational AI Engineer

R2 Technologies Corporation

Alpharetta, GA • On-site

Full-time

Re-posted 10 hours ago

Job description

Overview:
Description:
Our client is looking for a Conversational AI Engineer to design, implement, and enhance a conversational AI agent leveraging the latest advancements in Generative AI and Natural Language Processing (NLP).
This role will work closely with business stakeholders to understand user needs, analyze AI interactions, and develop intelligent, responsive chatbot experiences. The ideal candidate has experience with Dialogflow CX, Vertex AI, BigQuery, and Looker Studio, as well as a deep understanding of LLMs (Large Language Models), prompt engineering, and fine-tuning AI models.
Tasks:
Develop and optimize a Generative AI-powered virtual assistant to provide accurate, dynamic, and context-aware responses.
Leverage LLMs and fine-tuning techniques within Vertex AI for advanced conversational capabilities.
Implement and refine conversational experiences in Dialogflow CX, incorporating Playbooks and Tools for structured interactions.
Analyze chatbot performance using BigQuery and Looker Studio to identify areas for improvement and enhance response quality.
Create guided conversational flows and prompt engineering strategies to optimize AI responses.
Enhance AI reasoning and retrieval-augmented generation (RAG) techniques to improve the agent's ability to pull in relevant, up-to-date information.
Integrate Google Cloud Functions for seamless backend connectivity and automation.
Work with stakeholders to ensure AI solutions align with business goals and compliance requirements.
Monitor and iterate on AI model performance, implementing continual improvements based on user feedback and analytics.
Knowledge, Skills and Abilities Required:
Strong problem-solving skills and ability to work with both technical and non-technical stakeholders.
Skills Required:
Experience developing AI-powered chat bots or virtual assistants, preferably using Dialogflow CX and Vertex AI.
Strong understanding of Generative AI, LLMs, NLP, and prompt engineering techniques.
Proficiency in Google Cloud Services, including Vertex AI, BigQuery, Looker Studio, and Cloud Functions.
Familiarity with Dialogflow Playbooks and Tools for structured conversational AI development.
Experience analyzing AI performance metrics and improving model accuracy.
Ability to translate business needs into effective Generative AI solutions.
Bachelors or master's degree in computer science, Computer Information Systems, AI, or a related field
Skills Desired:
Familiarity with APIs, cloud security best practices, and AI ethics
Proficiency in Python or JavaScript for AI model integration and automation.
Experience with RAG-based AI approaches to improve knowledge retrieval in conversations.
Experience deploying infrastructure as code using Terraform.
Skills:
NLP

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