Time and Attendance is looking for a Data Scientist to deliver data insights for cross-functional projects to eliminate employee pay defects.
Time and Attendance (TAA) is a rapidly growing team tackling new, hard problems that Amazon has not solved at scale and creating fundamentally improved ways for employees to record time and receive accurate pay. We balance start-up vision and operational excellence, technical complexity and clear product definition, and global scope across multiple Amazon businesses. We are developing software solutions to support Amazon’s high-growth populations. We’ve all heard about 24/7/365. That’s 8760 hours in a year. Now multiply that by the hundreds of thousands of hourly workers at Amazon … those who work in our fulfillment, customer service, Alexa data services, and AWS data centers; employees in our growing number of Amazon Books bookstores and subsidiaries. On every continent. We must be able to move at Amazon speed and support new and varied business launches.
Who are we looking for to join our team?
At Amazon we take seriously our commitment to pay employees accurately and on-time. While each line of business is responsible for knowing and driving down pay defects for their own employees, the centralized TAA Perfect Pay team manages data stores and analytics, program oversight, cross-org technical and non-technical projects, and drives accountability across leaders. We are looking for a Data Scientist to identify and deliver data insights for cross-functional projects involving tools and processes to prevent pay defects before they happen.
The ideal candidate isan experienced and motivated Data Scientist (DS) with outstanding leadership skills, proven ability to build and manage medium-scale modeling projects, identify data requirements, and build methodology and tools that are statistically grounded. The candidate will be an expert in the areas of data science, machine learning and statistics, and is comfortable facilitating ideation and working from concept through to execution. The successful Data Scientist will have the extreme bias for action needed in a startup environment.
· Bachelor’s Degree
· 3+ years of experience with data scripting languages (e.g SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
· 2 years working as a Data Scientist
· Experience with statistical analysis, research science, machine learning and deep learning techniques, data modeling, regression modeling, financial analysis, and demand modeling.
· Excellent written and verbal communication skills. Strong ability to interact, communicate, present, and influence within multiple levels of the organization.
· Proficiency with QuickSight/Tableau/R Shiny/Dash or other web-based interfaces to create graphic-rich customizable plots, charts data maps etc.
· Previous experience in a ML or data scientist role with a large technology company.
· 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.
· Experience with AWS services (Redshift, S3, EC2, Lambda, SNS/SQS, RDS, Aurora) preferred.
· Ability to distill informal customer requirements into problem definitions, quantify improvement in customer experience or value for the business resulting from research outcomes, dealing with ambiguity and competing objectives.
· Experience with applying Machine Learning and Data Science in HR, Marketing, Advertising, or the social and behavioral sciences.
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