Data Scientist II - AMZ9803565

Amazon•Culver City, CA

20d•$158,808 - $184,000•Onsite

About The Position

The Data Scientist II will design and implement scalable and reliable approaches to support or automate decision-making throughout the business. This role involves applying a range of data science techniques and tools, combined with subject matter expertise, to solve complex business problems where the solution approach may not be immediately clear. The position requires acquiring data through SQL/ETL queries and importing processes using company-specific interfaces for Oracle, RedShift, and Spark storage systems. Building relationships with stakeholders and counterparts is crucial. The role includes analyzing data for trends and input validity, building models using various statistical, mathematical, and machine learning techniques, and validating these models against alternative approaches and key performance indicators. Implementation of models must consider computational demands, accuracy, and reliability within ETL processes.

Requirements

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.
Alternatively, a 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.
One year of experience in building statistical models and machine learning models using large datasets from multiple resources.
One year of experience in writing SQL scripts for analysis and data migration.
One year of experience in applying specialized modelling software including R, Python, or MATLAB.

Responsibilities

Design and implement scalable and reliable approaches to support or automate decision making throughout the business.
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.
Acquire data by building the necessary SQL / ETL queries.
Import processes through various company specific interfaces for accessing Oracle, RedShift, and Spark storage systems.
Build relationships with stakeholders and counterparts.
Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies.
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.
Validate models against alternative approaches, expected and observed outcome, and other business defined key performance indicators.
Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production.