Data Scientist, Ade Analytics

Amazon Amazon · Big Tech · CA, BC +1 · Applied Science

Data Scientist on the Alexa Daily Essentials team, focusing on analyzing complex data, developing statistical methodologies, and providing product insights to shape solutions. Responsibilities include problem-solving through data analysis and modeling, building data pipelines, acquiring data via SQL/ETL, and communicating complex ideas to technical and non-technical audiences.

What you'd actually do

  1. Analyze complex data to identify patterns, inform product decisions, and understand root causes of anomalies.
  2. Develop analysis and modeling approaches to drive product and engineering actions to identify patterns, insights, and understand root causes of anomalies. Your solutions directly improve the customer experience.
  3. Independently work with product partners to identify problems and opportunities. Apply a range of data science techniques and tools to solve these problems. Use data driven insights to inform product development. Work with cross-disciplinary teams to mechanize your solution into scalable and automated frameworks.
  4. Build data pipelines, and identify novel data sources to leverage in analytical work - both from within Alexa and from cross Amazon
  5. Acquire data by building the necessary SQL / ETL queries

Skills

Required

  • 2+ years of data scientist experience
  • 2+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
  • 2+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
  • Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)

Nice to have

  • Knowledge of machine learning concepts and their application to reasoning and problem-solving
  • Experience in Python, Perl, or another scripting language
  • Experience in a ML or data scientist role with a large technology company
  • Experience working on multi-team, cross-disciplinary projects
  • Experience applying quantitative analysis to solve business problems and making data-driven business decisions
  • Experience effectively communicating complex concepts through written and verbal communication

What the JD emphasized

  • complex data
  • statistical methodologies
  • product insights
  • scale data solutions
  • data pipelines
  • SQL / ETL queries
  • complex ideas

Other signals

  • develop statistical methodologies
  • provide critical product insights
  • build frameworks and mechanisms to scale data solutions