DESCRIPTION

Job summary
Have you ever wondered how Amazon selects the offer(s) for a given product from potentially hundreds of sellers selling the same item? It is one of the most critical models in Amazon and one of the most visible ones on the web. Whenever you see price, anywhere on Amazon, in any locale, it is calling this model at the backend. This is an opportunity to work with the team, Offers Experience, that develops and maintains this model. It drives one of the most coveted real estate in the e-commerce industry, the “Offer Display” across all surfaces (mobile app, mobile web, desktop, Alexa shopping) worldwide. The team’s vision is to simplify Amazon shopping experience by helping customers discover and evaluate offers to find the right option for their shopping journey. We use Machine Learning models to select, rank and feature the most relevant offers to customers. Our model serves hundreds of millions of Amazon customers and handles millions of requests per second for hundreds of millions of products and billions of offers across the world.

We are looking for an Economist to join this high impact, high visibility team. You will lead the development and expansion of the next generation of the featured offer selection models. These new models will incorporate the continually changing preferences of our customers and continue to scale with numerous new programs that Amazon is introducing for our customers. You will work with multiple Amazon businesses and programs to identify big business opportunities and propose new business features and technical systems to improve customer experience. As a team, we own the end-to-end life cycle of models – estimation, simulation and experimentation. Your work will cut across various sub-disciplines like Causal Inference, Bayesian Hierarchical Models, Counterfactual Estimation and Evaluation, Multi-armed Bandits, and High-dimensional Multivariate Experiments. You will be responsible for the quality of the model and will get the opportunity to present your ideas and share results of your deliverables with Amazon executives and Amazon scholars on a regular basis. As a Economist, you will be collaborating with other junior econmists to define and enforce broad, company-wide technical standards in statistical modelling, optimization and simulation techniques.

Why is this a great opportunity?
• We impact the global Amazon retail business: We are at the center of Amazon’s retail universe. We work closely with other Retail teams like, BuyX, Search, Pricing, Cart, Checkout, Delivery Experience, Ultra Fast Grocery, Subscribe-n-Save, etc. You build systems that are used every time a customer sees any item on the Amazon website (globally) and helps them to make purchase decisions. As a result, your work will earn and preserve the customer trust. Our impact is typically measured in hundreds of millions of dollars.
• We are diverse: Our team is diverse in terms of expertise (SDE/Scientists/Economists/Data Engineer/Product Manager), nationality (10 countries), experience (college grad to industry veteran), tech-stacks (AWS frontend and backend, Datapath), and office locations (Seattle, Bangalore, Berlin, Vancouver).
• We prioritize learning: Work alongside some of Amazon’s smartest engineers, scientists, economists, and product managers. We have one Principal Economist and two Principal SDEs in the team to learn from. We regularly take ML courses and present/teach at internal and external forums. We innovate, publish at Amazon Machine Learning Conference (AMLC), and file patents. We regularly review our models with academics like Michael Jordan, Guido Imbens, and our Chief Economist, Pat Bajari.
• We ensure work-life balance: Our team works together to provide work-life balance for all team members. We recognize that the circumstances of our team members vary, and we balance work across the team so that we are all able to maintain high standards on behalf of our customers, while at the same time allowing for rich and happy personal lives.
• We grow people: In H2 2021 alone, our org promoted 21 employees including a couple of L7 (principal) promotions.
• We have fun: We find ways to relax and unwind with team events and group lunches.
• We offer location flexibility: We are open to team members working from other locations as long as it is in the same country.

If you are ready to truly make an impact on a product that is used by hundreds of millions of people around the world, including your own friends and family, then we would love to talk to you.

BASIC QUALIFICATIONS

PhD in Economics or other quantitative closely related field

PREFERRED QUALIFICATIONS

a) Proficiency in Spark-Scala or Py-Spark b) Ability to work effectively within an interdisciplinary science team of economists, applied scientists, software engineers, and data engineers c) Ability to communicate relevant scientific insights from data to senior business leaders, financial analysts, and product managers d) Background/post-graduate training in causal inference e) One or more publications in peer-reviewed statistical journals f) Experience in implementing modern machine-learning methods (e.g., boosted regression trees, random forests, neural networks).