Applied Scientist

Description

Amazon Connections is an innovative program that gives Amazonians globally a way to give feedback on the workplace and help shape the future of the company. By asking employees quick questions every day, Connections leverages real-time information to learn more about their experiences and introduce positive changes with internal business partners around the world. Our goal is to help develop leaders who earn trust, remove barriers to excellence and make Amazon an inspiring place to work.

The Connections Research team is seeking a smart, driven, applied scientist to support innovative research practice at Amazon. This team member will be responsible for big data exploration. This candidate must demonstrate creativity, provide exceptional organizational skills, have excellent analytical skills, possess strong verbal and written communication skills, and be truly customer oriented. This role provides opportunity for significant exposure to Amazon's culture and global efforts to engage our employees.

Role Overview

The Applied Scientist will be responsible for developing algorithms that assist in evaluating the effectiveness of Connections questions for a number of outcomes. Responsibilities:

  • Assist in operationalizing econometric and statistical models
  • Perform model refreshes or updates to analyses as needed
  • Work collaboratively with economists and research scientists to assist in the design and implementation of analysis to answer challenging HR questions
  • Interpret and communicate results to outside customers
  • Drive operational excellence for data ingestion, transformation, and publication to ensure confidence in the systems we build
  • Aggregate and analyze data pulled from disparate sources (HR, Finance or other business systems) and related industry and external benchmarks; provide insights and a point of view on analysis and recommendations
  • Tune query performance using profiling tools and SQL
  • Assist in the design and delivery of automated, scalable analytical models to stakeholders
  • Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for secondary datasets
  • Report results in a manner which is both statistically rigorous and compellingly relevant

Basic Qualifications

  • Advanced Degree in a technical or analytical field (economics, math, statistics or data science)
  • 3-5 years of experience
  • Proficient in Python, R, or some combination
  • Knowledge in data analysis technologies (R/Python-Pandas, Numpy, Stats models, Scikit learn)
  • Advanced data analysis skills – e.g. database query construction, data warehousing, regression modeling, and experience in business analysis or consulting.
  • Experience building forecasting models related to workforce movement, customer relationship management, or sales
  • Ability to make recommendations for new metrics, strategies, and methods to improve measurement and data collection practices
  • Knowledge in SQL, databases and ETL jobs
  • Experience in building automated analytical systems utilizing large data sets
  • Self-starter with the ability to work independently
  • Great organizational skills and attention to detail; you prioritize multiple tasks simultaneously without sacrificing the ability to dive deep
  • Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner
  • Impeccable customer service focus with a demonstrated desire to exceed expectations; a team player with a solid work ethic

Preferred Qualifications

  • PhD degree in a technical or analytical field
  • Ability to educate others on statistical methods
  • Advanced knowledge and expertise with data modelling skills, advanced SQL with PostgreSQL and other Columnar Databases
  • Knowledge in Big Data Technologies (HDFS, Hive, Spark, etc.) for managing large datasets
  • Experience designing and implementing scalable ETL design and mappings, database query construction and data warehousing skills
  • Familiarity with Tableau, RedShift, EC2 and S3

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