Amazon Development Center U.S., Inc. - B02
Corporate Operations, Science, no business category
DataScientistII
“Data Scientist II at Amazon Development Center U.S., Inc. - B02. Skills: Data science, Machine learning, Statistical modeling, SQL. Design and implement scalable and reliable approaches. Support or automate decision making”
What You'll Achieve.
Support or automate decision making; Solve difficult business problems; Validate models against business defined key performance indicators
Industry & Context.
Solve difficult business problems; Analyze data; Model validation
What They're Looking For.
Must Have
Master's degree or foreign equivalent in Statistics, Applied Mathematics, Economics, Engineering, Computer Science, or related field and one year of experience, Bachelor's degree or foreign equivalent in Statistics, Applied Mathematics, Economics, Engineering, Computer Science, or related field and five years of progressive post-baccalaureate experience, One year of experience building statistical models and machine learning models, One year of experience writing SQL scripts for analysis and data, One year of experience applying specialized modeling software including R, Python, or MATLAB
What You'll Do.
Design and implement scalable and reliable approaches
Support or automate decision making
Apply data science techniques and tools
Solve difficult business problems
Acquire data by building SQL / ETL queries
Import processes through company specific interfaces
Build relationships with stakeholders and counterparts
Analyze data for trends and input validity
Inspect univariate distributions
Explore bivariate relationships
Construct appropriate transformations
Track down source and meaning of anomalies
Build models using statistical modeling
Build models using mathematical modeling
Build models using econometric modeling
Build models using network modeling
Build models using social network modeling
Build models using natural language processing
Build models using machine learning algorithms
Build models using genetic algorithms
Build models using neural networks
Validate models against alternative approaches
Validate models against expected and observed outcome
Validate models against business defined key performance indicators
Implement models that comply with evaluations
Evaluate computational demands
How You'll Work.
Team & Collaboration
Build relationships with stakeholders
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