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    Senior Economist, Global Talent Management and Compensation - Seattle, WA, United States - Amazon

    Amazon
    Amazon Seattle, WA, United States

    2 weeks ago

    Amazon background
    Description

    Senior Economist, Global Talent Management and Compensation

    Job ID: | Services LLC

    Amazon Global Talent Management and Compensation (GTMC) Center for Applied Science and Economics (CASE) builds science models supporting scalable science-powered employee experiences for Amazonians, conducts experiments for a wide range of employee and talent related product features, and measures impact of product and program initiatives in enhancing our employees career experience in Amazon.

    Amazon's GTMC team is looking for Senior Economists, who can work at the intersection of economics, statistics and machine learning; and engage in building advanced experimentation and evaluation capabilities that take care of nuances of policy evaluation in complex settings. Key job responsibilities
    The Senior Economists within GTMC, focus on enhancing causal evaluation, measurement and experimentation tasks to ensure various science integrations and interventions achieving their goals in building a more rewarding career for our employees. The senior economists develop and implement complex randomization designs that address the nuances of experimentation for complex settings in which multiple populations interact. Additionally, they engage in building a range of econometric models that surfaces the various proactive and reactive inspection signals aiming towards better alignment in implementation of various talent processes. The economists will closely collaborate with a range of scientists with different backgrounds as well as program and product leaders to implement and assess our science solutions into our products. We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA

    BASIC QUALIFICATIONS

    PhD in economics or equivalent
    - 2+ years in post-doctoral work experience.

    PREFERRED QUALIFICATIONS

    Experience in analytics and applied economics
    - Experience in building statistical models using R, Python, STATA, or a related software
    - Experience in industry, consulting, government or academic research
    - Experience in design and delivery of automated, scalable causal models
    - 4+ years in post-doctoral work experience.
    - Experience in Diversity, Equity, & Inclusion (DEI) analysis for the workforce

    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 Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $127,300/year in our lowest geographic market up to $247,600/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 This position will remain posted until filled. Applicants should apply via our internal or external career site.

    Posted: April 10, 2024 (Updated about 18 hours ago)

    Posted: April 12, 2024 (Updated 1 day ago)

    Posted: April 12, 2024 (Updated 1 day ago)

    Posted: April 12, 2024 (Updated 1 day ago)

    Posted: April 12, 2024 (Updated 1 day ago)

    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.

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