Business Data Scientist, Customer Voice, Analytics

Google Google · Big Tech · Mountain View, CA +3

This role focuses on developing and deploying NLP and machine learning models to extract insights from customer conversations for a Go-to-Market team. It involves identifying trends, predicting customer behaviors, and ensuring statistical rigor in reporting, with a focus on Large Language Models and prompt engineering.

What you'd actually do

  1. Design, train, and deploy NLP models and unsupervised machine learning algorithms to identify emerging trends and friction points within sales transcripts.
  2. Build predictive machine learning models that leverage text-derived features to forecast key outcomes.
  3. Apply robust statistical methods (e.g., confidence intervals, significance testing, sampling strategies) to your findings, ensuring the metrics and themes we report to product and GTM leadership are reliable and statistically sound.
  4. Transform complex NLP and ML outputs into clear, compelling narratives, effectively communicating the "so what" and the degree of certainty behind the data.

Skills

Required

  • NLP models
  • unsupervised machine learning algorithms
  • predictive machine learning models
  • statistical methods
  • Large Language Models
  • prompt engineering
  • fine-tuning techniques
  • Python
  • R
  • SQL

Nice to have

  • vector databases
  • embedding models
  • transformer models
  • clustering algorithms

What the JD emphasized

  • Experience working with Large Language Models, prompt engineering, and fine-tuning techniques.

Other signals

  • Develop models to extract nuanced themes and actionable signals from hundreds of thousands of customer conversations.
  • Apply core machine learning and statistical methods to cluster feedback, predict customer behaviors, and ensure our insights are reported with rigorous statistical confidence.
  • Design, train, and deploy NLP models and unsupervised machine learning algorithms to identify emerging trends and friction points within sales transcripts.
  • Build predictive machine learning models that leverage text-derived features to forecast key outcomes.