Java Programming, Python Programming, SQL, AWS, Machine learning techniques, Data science techniques, Tableau, Continuous Integration & Continuous Delivery - CI/CD, Data Analytics, R Programming, Amazon RedShift, Amazon EMR, Amazon Elastic Compute Cloud-EC2, AWS Sagemaker, Amazon Simple Storage Service (S3), Data pipelines, QuickSight, Kimball methodology, VR/AR frameworks
Amazon’s Worldwide Operations Consumer & Corporate (WWOC&C) Employee Relations (ER) team is looking for a Data Science Manager (DSM) 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 DSM will lead a new team that is pioneering ideas from concept to reality and in this role—new bold ideas are always welcome. This DSM will obsess over the Amazon employee experience and the employee voice across the organization. This DSM will directly apply their knowledge of Machine Learning, Natural Language Processing engines and Business acumen to dig deep and help Amazon leaders gain insights into areas of opportunity in the employee experience across Amazon. 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 Science Manager 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 Worldwide Operations Consumer & Corporate (WWOC&C) portfolio, and have direct impact on the daily work of over 1.5M+ 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
About the team
The Employee Relations team has one of the most broad and expansive remits in Amazon and is responsible for the identification of defects in our employee experience across all roles in the WWOC&C organization and beyond. Finding these defects is not enough though; we are tasked with building and deploying Programs, 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. Our ER Organization is highly empowered to do the right thing for our employees and is often called on to provide insight to the highest levels of leadership at Amazon.
Our team has a developed a reputation for attracting, developing, and retaining amazing talent from diverse backgrounds. Yes, we do get to build a really cool services and work closely with our customers, but we also think a big reason for our success is the inclusive and welcoming culture we try to cultivate every day. We’re looking for a new teammate who is enthusiastic, empathetic, curious, motivated, reliable, and able to work effectively with a diverse team of peers; someone who will help us amplify the positive & inclusive team culture we’ve been building.
BASIC QUALIFICATIONS
PREFERRED QUALIFICATIONS
Amazon Web Services, Inc. (AWS) is a subsidiary of Amazon providing on-demand cloud computing platforms and APIs to individuals, companies, and governments, on a metered pay-as-you-go basis. These cloud computing web services provide a variety of basic abstract technical infrastructure and distributed computing building blocks and tools. One of these services is Amazon Elastic Compute Cloud (EC2).
Canberra ACT, Australia
2-4 year
Sydney NSW, Australia
2-4 year
Vancouver, BC, Canada
2-4 year
Vancouver, BC, Canada
2-4 year
Vancouver, BC, Canada
2-4 year
Vancouver, BC, Canada
2-4 year
Vancouver, BC, Canada
2-4 year
Vancouver, BC, Canada
2-4 year
Shenzhen, Guangdong Province, China
2-4 year
Shenzhen, Guangdong Province, China
2-4 year
Berlin, Germany
2-4 year
Dublin, Ireland
2-4 year
Dublin, Ireland
2-4 year
Dublin, Ireland
2-4 year
Tel Aviv, Israel
2-4 year
Tel Aviv, Israel
2-4 year
Tel Aviv, Israel
2-4 year
Tel Aviv-Yafo, Israel
2-4 year
Bangalore, Karnataka, India
2-4 year
Bangalore, Karnataka, India
2-4 year
Gurgaon, Haryana, India
2-4 year
Gda?sk, Poland
2-4 year
Bay Area, CA, USA
2-4 year
Cupertino, CA, USA
2-4 year
Arlington, VA, USA
2-4 year
Arlington, VA, USA
2-4 year
Arlington, VA, USA
2-4 year
United States
2-4 year
Arlington, VA, USA
2-4 year
Arlington, VA, USA
2-4 year
Bellevue, WA, USA
4-6 year
Ballston, NY, USA
2-4 year
Berlin, MD, USA
2-4 year
Bellevue, WA, USA
2-4 year
California, USA
2-4 year
Charlotte, NC, U.S.
2-4 year
Charlotte, NC, USA
2-4 year
Charlotte, NC, USA
2-4 year
Chicago, IL, USA
2-4 year
Chicago, IL, USA
2-4 year
Chicago, IL, USA
2-4 year
Cupertino, CA, USA
2-4 year
Denver, CO, USA
2-4 year
East Palo Alto, CA, USA
2-4 year
East Palo Alto, CA, USA
2-4 year
Florida City, FL, USA
2-4 year
Herndon, VA, USA
2-4 year
Irvine, CA, USA
2-4 year
Minneapolis, MN, USA
2-4 year
New Jersey, USA
2-4 year
Pasadena, CA, U.S.
2-4 year
Pittsburgh, PA, USA
2-4 year
Pasadena, CA, USA
2-4 year
Portland, OR, USA
2-4 year
Portland, OR, USA
2-4 year
San Diego, CA, USA
2-4 year
San Francisco Bay Area, CA, USA
2-4 year
Santa Clara, CA, USA
2-4 year
Santa Clara, CA, USA
2-4 year
Santa Clara, CA, USA
2-4 year
Santa Monica, CA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, Washington, USA
2-4 year
Seattle, Washington, USA
2-4 year
Seattle, Washington, USA
2-4 year
Seattle, Washington, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Sunnyvale, CA, USA
2-4 year
United States
2-4 year
United States
2-4 year
United States
2-4 year
United States
2-4 year
Virginia Beach, VA, USA
2-4 year
Washington D.C., DC, USA
2-4 year
Washington D.C., DC, USA
2-4 year
East Palo Alto, CA, USA
2-4 year
Florida, USA
2-4 year
Santa Clara, CA, USA
2-4 year
Santa Clara, CA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
United States
2-4 year
United States
2-4 year
United States
2-4 year
United States
2-4 year
Cape Town, South Africa
2-4 year
Austin, TX, USA
2-4 year
Chicago, IL, USA
2-4 year
Dallas, TX, USA
2-4 year
Detroit, MI, USA
2-4 year
Houston, TX, USA
2-4 year
Minneapolis, MN, USA
2-4 year
Nashville, TN, USA
2-4 year
Phoenix, AZ, USA
2-4 year
Salt Lake City, UT, USA
2-4 year
Tempe, AZ, USA
2-4 year
London, UK
2-4 year
United States
2-4 year
Bellevue, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Santa Clara, CA, USA
2-4 year
Vancouver, BC, Canada
2-4 year
Vancouver, BC, Canada
4-6 year
Dallas, TX, USA
2-4 year
London, UK
2-4 year
New York, NY, USA
2-4 year
New York, NY, USA
2-4 year
New York, NY, USA
2-4 year
New York, NY, USA
2-4 year
New York, NY, USA
2-4 year
New York, NY, USA
2-4 year
San Francisco, CA, USA
2-4 year
San Francisco, CA, USA
2-4 year
San Francisco, CA, USA
2-4 year
San Francisco, CA, USA
2-4 year
Vancouver, BC, Canada
2-4 year
United States
2-4 year
Cupertino, CA, USA
2-4 year
Austin, TX, USA
4-6 year
Vancouver, BC, Canada
10-12 year
San Francisco, CA, USA
4-6 year
Toronto, ON, Canada
8-10 year
Washington D.C., DC, USA
2-4 year
San Francisco, CA, USA
4-6 year
Mono Hot Springs, CA, USA
4-6 year
Washington D.C., DC, USA
4-6 year
Arlington, VA, USA
6-8 year
Herndon, VA, USA
6-8 year
Seattle, WA, USA
6-8 year
Arlington, VA, USA
6-8 year
Herndon, VA, USA
6-8 year
Houston, TX, USA
6-8 year
Dallas, TX, USA
6-8 year
San Francisco, CA, USA
4-6 year
Seattle, WA, USA
4-6 year
Chicago, IL, USA
4-6 year
New York, NY, USA
4-6 year
Los Angeles, CA, USA
4-6 year
Mountain View, CA, USA
4-6 year
San Francisco, CA, USA
6-8 year
Santa Clara, CA, USA
6-8 year
Seattle, WA, USA
4-6 year
San Francisco, CA, USA
8-10 year
Miami, FL, USA
4-6 year
Santa Clara, CA, USA
6-8 year
Washington D. C., DC, USA
6-8 year
San Francisco, CA, USA
4-6 year
Arlington, VA, USA
4-6 year
Santa Clara, CA, USA
4-6 year
Washington D. C., DC, USA
4-6 year
New York, NY, USA
4-6 year
New Jersey Turnpike, Kearny, NJ, USA
4-6 year