Job Description

DESCRIPTIONAre 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 within IES Shopping Intelligence org. 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 modelsWe 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:
\xc2\xb7 Data warehousing and EMR (Hive, Pig, R, Python).
\xc2\xb7 Feature extraction, feature engineering and feature selection.
\xc2\xb7 Machine learning, causal inference, statistical algorithms and recommenders.
\xc2\xb7 Model evaluation, validation and deployment.
\xc2\xb7 Experimental design and testing.BASIC QUALIFICATIONS- 4+ 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 regressionPREFERRED QUALIFICATIONS- -Experience processing, filtering, and presenting large quantities (100K to Millions of rows) of data
- -Experience with statistical analysis, data modeling, machine learning, optimizations, regression modeling and forecasting, time series analysis, data mining, and demand modeling
- -Experience applying various machine learning techniques, and understanding the key parameters that affect their performance
- -Excellent written and verbal communication skills. Strong ability to interact, communicate, present, and influence within multiple levels of the organization.
- - Experience in an operational environment developing, fast-prototyping, piloting and launching analytic products
- -Experience in writing academic-styled papers for presenting both the methodologies used and results for data science projects.
- - Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately understand cause and effect relations
- -Experience in creating data driven visualizations to describe an end-to-end system
- -Excellent written and verbal communication skills. The role requires effective communication with colleagues from computer science, operations research and business backgrounds.
- -Ability to work on a diverse team or with a diverse range of coworkers

Amazon