Principal Applied Scientist, Ads Optimization, Faim

Amazon Amazon · Big Tech · Palo Alto, CA · Applied Science

Principal Applied Scientist role focused on inventing and productionizing machine learning and optimization models for full-funnel ad campaign optimization at Amazon. This includes joint budget allocation, incrementality measurement, and long-term sales modeling, taking innovations from research to production at scale. The role involves defining scientific vision, partnering with engineering and product, and raising the technical bar.

What you'd actually do

  1. Define the long-term scientific vision for full-funnel campaign optimization, translating ambiguous advertiser needs and competing objectives into a concrete science roadmap.
  2. Invent, prototype, and productionize machine learning and optimization solutions for joint budget allocation across sponsored ad products, spanning the shopper journey from awareness to purchase.
  3. Develop rigorous approaches to incrementality measurement and long-term-sales modeling that ground optimization in true advertiser value.
  4. Design and lead large-scale experiments and analyses to validate hypotheses and guide product direction.
  5. Partner closely with engineering and product to define technical contracts, data schemas, and serving systems that carry models into production.

Skills

Required

  • PhD in Electrical Engineering, Computer Science, Mathematics, or a related technical field
  • 5+ years of hands-on experience in predictive modeling and analysis
  • Experience distilling informal customer requirements into problem definitions while dealing with ambiguity and competing objectives
  • Experience programming in Java, C++, Python, or related language
  • Experience leading experienced scientists, as well as a record of developing junior members from academia or industry into a career track in a business environment

Nice to have

  • 10+ years of relevant experience in industry or academia
  • Knowledge of problem solving, algorithm design, and complexity analysis
  • Experience creating novel algorithms and advancing the state of the art
  • Peer-reviewed scientific contributions in premier journals and conferences

What the JD emphasized

  • invent foundational optimization science where little exists today
  • take models from research to production at Amazon scale
  • directly move advertiser ROAS and new-to-brand growth
  • invent, prototype, and productionize machine learning and optimization solutions
  • develop rigorous approaches to incrementality measurement and long-term-sales modeling
  • publish impactful research internally and at top-tier venues

Other signals

  • invent foundational optimization science
  • models from research to production at Amazon scale
  • directly move advertiser ROAS and new-to-brand growth
  • define the long-term scientific vision
  • invent, prototype, and productionize machine learning and optimization solutions
  • develop rigorous approaches to incrementality measurement and long-term-sales modeling
  • partner closely with engineering and product to define technical contracts, data schemas, and serving systems
  • grow scientific talent and publish impactful research