Data Scientist, Employee Relations

Job summary
Amazon’s Employee Relations (ER) team is looking for a Data Scientist (DS) with a demonstrated passion for building innovative new analytics, models, tools and processes for our Employees and Leaders. Are you looking for an opportunity to build in a completely new space that will stretch you and force you to demonstrate your mastery of data science, data analytics, problem solving and enterprise wide deployments? This DS will lead new pioneering ideas from concept to reality and in this role—new bold ideas are always welcome. This DS will obsess over the Amazon employee experience and the employee voice across the organization. This DS will directly apply their knowledge of Natural Language Processing engines to dig deep and help Amazon leaders gain insights from hundreds of thousands of comments from our employees. Finding, prioritizing and resolving employee experience defects will be the mission every day. Thus, the challenge of this role is that it is never complete; we will always strive to push Amazon to be the Earth’s best employer.
The Data Scientist will play a critical role in advancing our mission. You will join a tight-knit team of ER professionals, including HR, operational, program, product, tech and legal leaders. You will be supporting Amazon's World Wide Corporate, Consumer and Operations (WWCC & Ops) portfolio, and have direct impact on the daily work of over 1.3M+ Amazonians.
Our projects span multiple organizations and require coordination of experimentation, economic and causal analysis, forecasting, dashboarding and predictive machine learning tools. We’re looking for an enthusiastic technical expert and storyteller to explore the world of Amazon data to generate insights—connecting employee experiences to decision makers in a compelling way backed by data. Your focus will cover all aspects of how we learn more about our employees, uncover problems that need to be solved, and validating the impact of our solutions. You will work with other thinkers, creators, and communicators to build the skills of the entire team to create a research-driven organization. You will invent, refine solutions from start to finish—data sets, queries, models, reports, dashboards, analyses—to answer business questions while ensuring we are meeting the needs of the business and team goals. You will draw on your knowledge of data science best practices, big data management fundamentals, and analysis principles to build solutions that enable effective, data-driven business decisions. You will learn the business context and technologies behind your team’s data infrastructure and work with customers (e.g., researchers, economists, data engineers, business intelligence engineers, product managers) and other internal partners to ensure deliverables are aligned with expectations.

If you love getting to the “a-ha” moment, when the solution to a customer or employee problem reveals itself in the data— let’s talk


Key job responsibilities
• Own the design, development, and maintenance of scalable solutions for analyses and models focused on Natural Language and free text inputs.
• Create innovative, sophisticated analytic models to address critical issues but also meet key business criteria (cost/risk/business impact) and key technical criteria (reliability/validity/predictability)
• Lead technical aspects of experiment design in collaboration with the greater ER team.
• Find and create ways to measure the workforce experience at multiple levels in the organization.
• Identify and advocate for technical options related to machine learning, data mining, and other statistical approaches
• Document feasibility requirements, code comments and other technical documentation required to transfer knowledge to other technical staff and management
• Write queries and have in-depth knowledge of the data available in area of responsibility.
• Troubleshoot operational data-quality issues and review/audit existing ETL jobs and queries.
• Collaborate on developing effective Dashboards to surface insights to senior leadership
• Communicate pros and cons of analytic frameworks to the development team
• Uncover drivers, impacts, and key influences on productivity and innovation outcomes
• Develop predictive and optimization models for key applications
• Navigate a variety of data sources, such as open text comments, survey results and free text fields inputs
• Ability to work in a highly collaborative environment with peers that have a range of technical aptitudes
• Maintain an understanding of the latest trends in data science and machine learning
• Recommend improvements to back-end data sources for increased accuracy and simplicity.


About the team
The Employee Relations team is responsible for the identification of defects in our employee experience across all roles in the WWC & Ops organization and beyond. Finding these defects is not enough though; we are tasked with building and deploying products, tools and solutions to remove these defects. Our products and programs are always changing and we continually innovate to transform and improve the employee experience

Basic Qualifications

• 3+ years of industry experience in role(s) like: Data/Business Analyst, Data Engineer, Business Intelligence, Data Scientist, or equivalent.
• 3+ years of data modeling, ETL management, and data warehousing experience.
• Demonstrated proficiency with data querying with SQL
• Demonstrated proficiency with data modeling techniques in R or Python
• Knowledge and direct experience using and deploying business intelligence reporting tools. (Quicksights, Tableau, Microstrategy, Excel etc.)

Preferred Qualifications

• Masters in computer science, mathematics, statistics, economics, or other quantitative fields.
• Experience working with AWS big data technologies (Redshift, S3, EMR).
• Experience with Stata, SAS, or Python.
• Experience in data modeling, ETL development, and data warehousing.
• Familiarity with statistical models and data mining algorithms.
• Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations



Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.