Data Scientist – Conversational AI Analytics

Nexiva • Rockville, MD

3d • Hybrid

About The Position

We are seeking a highly analytical and technically skilled Data Scientist to help drive insights from conversational AI platforms and large-scale interaction data. This role focuses on extracting actionable intelligence from AI-generated conversations through advanced clustering, embedding analysis, LLM-assisted categorization, and analytics engineering. The ideal candidate combines expertise in machine learning, natural language processing (NLP), data engineering, and cloud-native analytics to uncover user behavior patterns, emerging topics, and operational insights that directly influence product strategy and platform evolution. This role partners closely with engineering, product, AI/ML, and business stakeholders to improve conversational AI experiences through data-driven decision making.

Requirements

• Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related technical discipline
• 5+ years of experience in data science, machine learning, NLP, or large-scale analytics engineering
• Strong proficiency in Python and data science ecosystems (Pandas, NumPy, Scikit-learn, PySpark, etc.)
• Experience with NLP, semantic embeddings, vector similarity, and clustering techniques
• Hands-on experience with LLMs, prompt engineering, and AI-assisted analytics workflows
• Experience building cloud-native analytics solutions in AWS, Azure, or GCP
• Strong SQL and data modeling skills
• Experience developing scalable analytical pipelines and automated workflows
• Ability to communicate complex analytical concepts to both technical and business audiences

Nice To Haves

• Experience with conversational AI platforms, chatbot analytics, or AI interaction telemetry
• Experience with vector databases, semantic search platforms, or retrieval systems
• Familiarity with distributed data processing technologies such as Spark or Ray
• Experience with orchestration frameworks such as Airflow or Step Functions
• Knowledge of MLOps, experiment tracking, and model governance practices
• Exposure to responsible AI, AI governance, or regulatory environments
• Experience building dashboards and data visualizations using BI tools or custom analytics platforms

Responsibilities

• Extracting actionable intelligence from AI-generated conversations through advanced clustering, embedding analysis, LLM-assisted categorization, and analytics engineering.
• Uncovering user behavior patterns, emerging topics, and operational insights that directly influence product strategy and platform evolution.
• Partnering closely with engineering, product, AI/ML, and business stakeholders to improve conversational AI experiences through data-driven decision making.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior