Data Scientist II - Amz27351.1

Amazon Amazon · Big Tech · San Francisco, CA · Corporate Operations

Data Scientist II at Amazon Web Services responsible for designing and implementing scalable data science approaches, acquiring and analyzing data, and building and validating statistical and machine learning models. The role involves working with large datasets, SQL/ETL, and various modeling software.

What you'd actually do

  1. Design and implement scalable and reliable approaches to support or automate decision making throughout the business.
  2. Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the solution approach is unclear.
  3. Acquire data by building the necessary SQL / ETL queries.
  4. Build models using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks.
  5. Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production.

Skills

Required

  • Master’s degree or foreign equivalent degree in Statistics, Applied Mathematics, Economics, Engineering, Computer Science, or a related field and one year of experience in the job offered or a related occupation.
  • Bachelor’s degree or foreign equivalent degree in Statistics, Applied Mathematics, Economics, Engineering, Computer Science, or a related field and five years of progressive post-baccalaureate experience in the job offered or a related occupation as equivalent to the Master’s degree and one year of experience.
  • building statistical models and machine learning models using large datasets from multiple resources
  • writing SQL scripts for analysis and data migration
  • applying specialized modelling software including R, Python, or MATLAB

What the JD emphasized

  • building statistical models and machine learning models using large datasets from multiple resources
  • writing SQL scripts for analysis and data migration
  • applying specialized modelling software including R, Python, or MATLAB

Other signals

  • design and implement scalable and reliable approaches to support or automate decision making
  • apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems
  • build models using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks