Data Scientist III - Amz9971313

Amazon Amazon · Big Tech · Seattle, WA · Corporate Operations

Data Scientist III role focused on owning data science elements of products, including data-based decision making, performance optimization, and tracking. Responsibilities include working with product managers, translating business problems into data requirements, initiating and owning analysis, modeling, system design, and development of data science solutions, and communicating results. Requires experience in building statistical and machine learning models, complex data analyses using scripting languages (Python, Java), and communication for requirements gathering and process development.

What you'd actually do

  1. Own the data science elements of various products to help with data-based decision making, product performance optimization, and product performance tracking.
  2. Work directly with product managers to help drive the design of the product.
  3. Work with Technical Product Managers to help drive the build planning.
  4. Translate business problems and products into data requirements and metrics.
  5. Initiate the design, development, and implementation of scientific analysis projects or deliverables.
  6. Own the analysis, modelling, system design, and development of data science solutions for products.
  7. Write documents and make presentations that explain model/analysis results to the business.
  8. Bridge the degree of uncertainty in both problem definition and data scientific solution approaches.
  9. Build consensus on data, metrics, and analysis to drive business and system strategy.

Skills

Required

  • building statistical models
  • machine learning models
  • large datasets
  • multiple resources
  • complex data analyses
  • scripting languages
  • Python
  • Java
  • communicating requirements
  • evaluating alternatives
  • developing processes
  • developing tools

What the JD emphasized

  • building statistical models and machine learning models using large datasets from multiple resources
  • building complex data analyses by leveraging scripting languages including Python, Java, or related scripting language
  • communicating with users, technical teams, and management to collect requirements, evaluate alternatives, and develop processes and tools to support the organization

Other signals

  • data-based decision making
  • product performance optimization
  • product performance tracking
  • data requirements and metrics
  • analysis, modelling, system design
  • data science solutions