Data Scientist, Automated Benchmarking

Job description

DESCRIPTION

Amazon Benchmarking is seeking a Data Scientist who will be a key contributor in defining new ways that measure the customer experience and performance of Amazon digital products around the world. This is cutting edge technology and an opportunity to exercise your creativity exploring unconventional ideas to simulate and quantify any aspect of the customer experience.

Joining a small team of scrappy hardware, software, and data engineers, you will use your skills to leverage computer vision algorithms, robotics, TCP traffic analysis, Machine Learning, and quantitative analysis to challenge conventional wisdom with hard data. Our ideal candidate loves data and metrics, is self-directed, knows how to get things done, and is not afraid to take on big challenges.
Are you this person? If so, you are going to love this job because you will:
· Solve unique problems and work on a small, self-directed team.
· Work in a cool set of technologies such as robotics and video, with all the algorithms and data that come with it
· Directly influence the vision and objectives for your team's work in alignment with business and market needs
· Directly change what we do in Amazon products to delight our customers

A qualified candidate demonstrates ability to manage medium-scale modeling projects, identify data requirements and build methodology and tools that are statistically grounded. This candidate will have a wide range of basic quantitative skills to investigate problems quickly and identify next steps required to reach an optimal solution, often using Machine Learning techniques. The ideal candidate will have experience collaborating with team members and across organizational boundaries. For this candidate, learning new tools and supporting the team are passions; new methods and technologies are accessible and sought out. Testing theories and using results to drive future work is natural.

Desired profile

BASIC QUALIFICATIONS

· Master's degree in Statistics, Applied Math, Data Scientist or a related quantitative field.
· Proficient with data analysis and modeling software such as Spark, R, etc.
· Proficient with using scripting language such as Python and data manipulation/analysis libraries such as Scikit-learn and Pandas for analyzing and modeling data.
· Experienced in using multiple data science methodologies to solve complex business problems.
· Experienced in handling large data sets using SQL and databases in a business environment.
· Excellent verbal and written communication.