Amazon's Weblab team enables experimentation at massive scale to help Amazon build better products for customers. A/B testing is in Amazon's DNA and we're at the core of how Amazon innovates on behalf of customers. We are seeking a skilled and experienced Economist to help us build the future of experimentation systems at Amazon.
You have an entrepreneurial spirit and want to make a big impact on Amazon and its customers. You are excited about cutting-edge research on causal inference. You enjoy complex experiments and innovative research on inference but also have a bias for delivering simple solutions to complex problems. You're looking for a career where you'll be able to design methodologies, to deliver, and to impress. You're a thought leader and you demonstrate this by delivering solutions, not just by having ideas. You challenge yourself and others to come up with better solutions. You develop strong working relationships and thrive in a collaborative team environment.
About us together:
We're going to help Amazon make better long term decisions by designing and delivering A/B-testing systems for long-term experiments, and by using these systems to figure out how near term behavior impacts long term growth and profitability. Our work will inform some of the biggest decisions at Amazon. Along the way, we're going to face seemingly insurmountable challenges. We're going to argue about how to solve them, and we'll work together to find a solution that is better than each of the proposals we came in with. We'll make tough decisions, but we'll all understand why. We'll be the dream team.
We have decades of combined experience on the team in many areas of science and engineering so it's a great environment in which to learn and grow. A/B testing is one of the hottest areas of research and development in the world today and this is a chance to learn how it works in the company known for pioneering its use.
Ideal candidate profile
· PhD in Economics or related field
· 5+ years of combined industry and academic experience in economics or applied science
· Experience with causal inference and designing complex experiments
· Highly motivated self-starter with bias for innovative thinking
· Excellent written and oral communication skills
· Experience with R, Python, Stata, or similar