Applied Scientist Ii, Amazon Business, Amazon Business - Gtmo Science

Amazon Amazon · Big Tech · M, Spain +1 · Applied Science

Applied Scientist II role at Amazon Business focused on revolutionizing sales productivity using AI-powered solutions. The role involves developing tools for Account Executives (AEs) to prioritize accounts, recommend products, and engage customers more effectively. It leverages machine learning and Generative AI to outreach customers based on their behavior and purchase history, and performs text mining on customer conversations to recommend solutions. The scientist will partner with product, tech, and sales teams to launch and scale global AI products, with a focus on improving customer experience and sales efficiency.

What you'd actually do

  1. primarily leverage machine learning techniques and generative AI to outreach customers based on their life cycle stage, behavioral patterns, and purchase history.
  2. perform text mining and insight analysis of real-time customer conversations and make the model learn and recommend the solutions.
  3. partner with product management and technical leadership to identify opportunities to innovate customer journey experiences.
  4. Design and lead large projects and experiments from beginning to end, and drive solutions to complex or ambiguous problems
  5. Build models that measure incremental value, predict growth, define and conduct experiments to optimize engagement of AB customers, and communicate insights and recommendations to product, sales, and finance partners.

Skills

Required

  • PhD, or a Master's degree and experience in CS, CE, ML or related field
  • Experience in patents or publications at top-tier peer-reviewed conferences or journals
  • Experience with programming in Python language
  • Experience in solving business problems through machine learning, data mining, Reinforcement learning and statistical algorithms

Nice to have

  • Technical fluency; comfort understanding and discussing architectural concepts and algorithms, schedule tradeoffs and new opportunities with technical team members.
  • Excellent critical thinking skills, combined with the ability to present your beliefs clearly and compellingly in both verbal and written form.

What the JD emphasized

  • improve the productivity and efficiency of AEs
  • expanding GenAI capabilities and scaling its impact
  • outreach customers based on their life cycle stage, behavioral patterns, and purchase history
  • text mining and insight analysis of real-time customer conversations
  • recommend the solutions
  • improve our customers’ experience when using AB
  • build and manage medium-scale modeling projects
  • identify data requirements
  • build methodology and tools that are statistically grounded
  • solve complex problems using machine learning (ML) and Generative AI techniques
  • hands-on experience making the right decisions about technology, models and methodology choices
  • prototype and test new ideas, iterate quickly, and deploy models to production
  • conduct in-depth data analysis and feature engineering to build robust ML models

Other signals

  • improve the productivity and efficiency of AEs
  • expanding GenAI capabilities and scaling its impact
  • outreach customers based on their life cycle stage, behavioral patterns, and purchase history
  • text mining and insight analysis of real-time customer conversations
  • recommend the solutions