Amazon

Data Scientist III, IES Shopping Intelligence

Job Description

Are you excited about delighting millions of customers by driving the most relevant marketing initiatives? Do you thrive in a fast-moving, large-scale environment that values data-driven decision making and sound scientific practices?
Amazon is seeking a Data Scientist . This team is focused on driving key priorities of a)core shopping that elevates the shopping CX for all shoppers in all lifecycle stages, b) developing ways to accelerate lifecycle progression and build foundational capabilities to address the shopper needs and c)Alternate shopping models

We are looking for a Data Scientist to join our efforts to support the next generation of analytics systems for measuring consumer behavior using machine learning and econometrics at big data scale at Amazon. You will work machine learning and statistical algorithms across multiple platforms to harness enormous volumes of online data at scale to define customer facing products and measure customer responses to various marketing initiatives.

The Data Scientist will be a technical player in a team working to build custom science solutions to drive new customers, engage existing customers and drive marketing efficiencies by leveraging approaches that optimize Amazon’s systems using cutting edge quantitative techniques.

The right candidate needs to be fluid in:
· Data warehousing and EMR (Hive, Pig, R, Python).
· Feature extraction, feature engineering and feature selection.
· Machine learning, causal inference, statistical algorithms and recommenders.
· Model evaluation, validation and deployment.
· Experimental design and testing.- 8+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
- 7+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- Experience with statistical models e.g. multinomial logistic regression


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