AI Research Scientist: Optimizing Ecommerce Experience

4 days ago


Étreux, Hauts-de-France, United States Chewy Full time

At Chewy, we are looking for an AI Research Scientist to join our Sponsored Ads team. This is a unique opportunity to drive innovation in ecommerce advertising and make a significant impact on customer experience.

Company Overview

We are a leading online retailer of pet products and accessories. Our mission is to provide the best possible experience for our customers and their pets. We are committed to equal opportunity and value diversity and inclusion.

Job Description

You will work with our cross-functional team to develop and implement machine learning models that optimize ecommerce experience for our customers. This includes simplifying shopping experiences, maximizing reach and discovery of new products, and creating a win-win ecosystem for shoppers, brand owners, and Chewy.

Key Responsibilities

  • Deploy machine learning and data science to simplify shopping experience for pet-parents
  • Maximize reach and discovery of new products of Chewy vendors
  • Create a win-win ecosystem for shoppers, brand owners, and Chewy
  • Ideate, implement, test, validate, and monitor various new models end-to-end to improve Chewy product offerings and advance applied science applications
  • Publish research papers in leading ML/AI/Advertising conferences solving problems for scale using innovative modeling
  • Establish high bar on model performance, establish applied-science implementation best practices, and mentor junior scientists
  • Deploy solutions at Chewy scale improving overall customer engagement and value for Pet Parents

What You'll Need

To succeed in this role, you will need:

  • An advanced degree (M.S., PhD, or equivalent experience) in Operations Research, Statistics, Applied Mathematics, Data Science, or related field
  • 3+ years' experience designing optimization and machine learning solutions for large-scale applications
  • Ability to understand and apply advanced mathematics and DS methodologies
  • Experience in building distributed pipelines, tuning, optimizing, and evaluation
  • Experience with multiple techniques including Predictive Models (Time Series and Regression), Linear Programming, and Classification, Search, Ranking, or large-scale embeddings
  • Ability to translate complex data sets and research into simple business recommendations

Estimated Salary

$120,000 - $180,000 per year, depending on experience and qualifications



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