GenAI Data Scientist, Real-Time Virtual Agent Tools

Asurion; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

Asurion is seeking a Data Science & Applied AI professional to build real-time AI tools for call center agents across voice and messaging channels. You will collaborate with product, engineering, and analytics to deploy GenAI-powered solutions that improve customer interactions.

The role emphasizes experimentation with LLMs, KPIs, and delivering production-grade AI features. A master’s degree and 1–2 years in AI/ML are preferred, with Python and cloud deployment skills.

Qualifications

• Requires a master’s degree in analytics, computer science, electrical engineering, computer engineering, or related advanced analytical fields.
• 1–2 years of work experience in AI/ML modeling; Gen AI experience is a plus.
• Solid knowledge in Python and NLP techniques; experience with embeddings, GPT, or Transformer models.
• Knowledge of cloud computing and AI deployment (AWS, Google Cloud).

Responsibilities

• Build proactive, real-time AI tools to assist call center agents across voice and messaging channels.
• Measure and analyze the impact of these solutions across thousands of interactions daily.
• Experiment with latest generative LLMs to build new GenAI applications and optimize cost vs performance.
• Design and iterate GenAI prompts based on performance metrics and user feedback.
• Deliver end-to-end reliable and scalable AI features in production.

Skills

ML & AI

LLMs

GenAI

Problem solving

Education

Master’s degree in analytics/CS/EE/CE

1–2 years AI/ML modeling

Tools

Python

Cloud (AWS/Google Cloud)

NLP frameworks

Embeddings/Transformer models

Job description

Asurion is seeking a Data Science & Applied AI professional to build real-time AI tools for call center agents across voice and messaging channels. You will collaborate with product, engineering, and analytics to deploy GenAI-powered solutions that improve customer interactions.

The role emphasizes experimentation with LLMs, KPIs, and delivering production-grade AI features. A master’s degree and 1–2 years in AI/ML are preferred, with Python and cloud deployment skills.