Applied Scientist, Ads Econ

Amazon Amazon · Big Tech · NY +1 · Applied Science

Applied Scientist role at Amazon Advertising focusing on building full life-cycle machine learning solutions, including scaling ad performance insights through agentic systems/LLMs. The role involves hands-on analysis, modeling with large datasets, productionizing ML models with engineers, running A/B experiments, and researching innovative ML approaches to drive monetization and sales for Amazon's advertising products.

What you'd actually do

  1. Build full life-cycle machine learning solutions; build models and perform data analysis to deliver scalable solutions to business problems.
  2. Scale ad performance insights through agentic systems/LLMs.
  3. Perform hands-on analysis and modeling with enormous data sets to develop insights that increase traffic monetization and merchandise sales without compromising shopper experience.
  4. Work closely with software engineers on detailed requirements to productionize the ML models you build.
  5. Run A/B experiments that affect hundreds of millions of customers, evaluate the impact of your optimizations and communicate your results to various business stakeholders.

Skills

Required

  • PhD or equivalent Master's Degree plus 4+ years of experience in CS, CE, ML or related field
  • 3+ years of experience of building machine learning models for business application
  • Experience programming in Python or related language

Nice to have

  • Experience using Unix/Linux
  • Experience in professional software development
  • PhD
  • algorithms and data structures
  • parsing
  • numerical optimization
  • data mining
  • parallel and distributed computing
  • high-performance computing
  • patents or publications at top-tier peer-reviewed conferences or journals

What the JD emphasized

  • build full life-cycle machine learning solutions
  • agentic systems/LLMs
  • enormous data sets
  • productionize the ML models
  • A/B experiments
  • scalable, efficient, automated processes
  • Research innovative machine learning approaches

Other signals

  • build full life-cycle machine learning solutions
  • Scale ad performance insights through agentic systems/LLMs
  • Perform hands-on analysis and modeling with enormous data sets
  • Work closely with software engineers on detailed requirements to productionize the ML models
  • Run A/B experiments
  • Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving
  • Research innovative machine learning approaches