Global Talent Management (GTM) is centrally responsible for creating and evolving Amazon’s talent programs and processes. Analytics is a growing start-up team inside of GTM with a direct impact on 300,000+ Amazonians across all of our businesses and locations around the world. We regularly use data to pitch ideas and drive conversations with Amazon’s Senior Vice President of HR and other executives about how to improve existing talent programs like Career Development and the Annual Review or invent new ones that address the evolving needs of our diverse employee base.
GTM is looking for experienced analysts to own the end-to-end measurement and evaluation strategy implementation for our new and evolving talent products. In this role, you will align directly with a product owner, influencing product design, data capture, reporting/measurement, and evaluation strategies. You will use existing data/research to identify new challenges and opportunities, as well as data collected through methods you create/define. You will leverage your subject matter expertise and strong written/verbal communications skills to develop reproducible research/analyses shared with HR analysts embedded across Amazon’s diverse set of businesses. As the end-to-end analyst for the product, you will also build proof-of-concept reporting tools, while scaling ad hoc data access, enabling the product team to make informed decisions in a fast-paced, ambiguous business environment.Responsibilities
· Align with product owners to translate business issues into testable hypotheses answerable with data
· Develop and execute analyses to drive talent insights
· Create data capture and measurement strategies that drive business action
· Drive a roadmap from descriptive to predictive analytics
· Work closely with peers and stakeholders to access, pull, transform, and analyze data from a variety of HR sources
· Gather new data, and/or creatively use existing data to propose metrics and present them in compelling but easily understood way to a non-statistical audience.
· Apply statistical tests to data, including (but not limited to), t-tests, chi-square, and regression.
· Compile results in a concise, meaningful, and actionable format and share findings to senior leadership
· Build processes to scale fast and accurate on-demand and ad hoc data/analytical requests for leadership and key stakeholders