Description
Do you have a passion for deriving insights from data to make a difference in people's lives? Are you a Day 1 thinker who is passionate about pushing the boundaries of conventional talent development approaches and innovating on behalf of our customers? If so, we would like to hear from you!
PATOE is a centralized technology, data, reporting, and analytics organization that supports over a million employees globally, spanning support across NA Customer Fulfillment, Global Operations Learning & Development and PXT Capability & Impact, and Employee Relations.
We are seeking a DS who 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 to dig deep and help Amazon leaders gain actionable insights. 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 PXT 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 validate 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.
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
2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
Experience applying theoretical models in an applied environment
Preferred Qualifications
Experience in Python, Perl, or another scripting language
Experience in a ML or data scientist role with a large technology company
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $125,500/year in our lowest geographic market up to $212,800/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.
