Applied Scientist for Media Planning Science

4 weeks ago

Toronto, Ontario, Canada Amazon Full time
About the Role

Amazon is seeking an accomplished and visionary machine learning expert to lead the Applied Science strategy for our Media Planning Science program. As an Applied Scientist, you will work closely with business leaders, stakeholders, and cross-functional teams to drive program success through ML-driven solutions.

Key Responsibilities
  • Serve as the technical leader in Machine Learning, guiding efforts within the team and collaborating with other teams.
  • Conduct hands-on analysis and modeling of large-scale data to generate insights that boost traffic monetization and merchandise sales while maintaining a positive shopper experience.
  • Lead end-to-end Machine Learning projects that involve high levels of ambiguity, scale, and complexity.
  • Build, experiment, optimize, and deploy machine learning models, collaborating with software engineers to bring your models into production.
  • Run A/B experiments, gather data, and perform statistical analysis to validate your models.
  • Develop scalable and automated processes for large-scale data analysis, model development, validation, and serving.
  • Explore and research innovative machine learning approaches to push the boundaries of what's possible.
About the Team

The Media Planning Science team builds and deploys models that provide insights and recommendations for media planning. Our mission is to assist advertisers in activating plans that align with their goals. Our insights and recommendations leverage heuristic and machine learning models to simplify the complex tasks of forecasting, outcome prediction, budget planning, optimized audience selection, and measurements for media planners.

Requirements
  • 3+ years of building models for business application experience
  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
  • Experience programming in Java, C++, Python or related language
  • Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
  • Experience using Unix/Linux
  • Experience in professional software development
  • Experience building machine learning models or developing algorithms for business application

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