Job Description
Our Opportunity: Advertising is a critical component of the ecommerce ecosystem and provides a critical revenue stream to the company. At Chewy we are building a 'new' team to launch a Sponsored Advertising business and looking for a Machine Learning Engineer III.
As an early member to the newly setup Sponsored Advertising team, you'll be part of core leadership team and will influence technical strategy across product search and discovery, relevance and ranking, prediction, and auction of large selection of sponsored products in Chewy catalog. You'll be at forefront of driving technology driven business impact. Machine learning and deep-learning models will influence selection, relevance, ranking, click-through prediction modelling, auction-dynamics, keywords recommendation, campaign optimization and wide array of engaging data-science groundbreaking methodologies.
Sponsored Ads creates a great outcome for everyone ecosystem for shoppers, brand owners and Chewy! Shoppers (pet Parents) are offered a range of alternate options to help them choose better and learn about new products, new brands, new promotions, and different price points. Brand owners and advertisers get to showcase their product offerings in the front row for their target audience (proud pet owners) and improve their reach.
Come be part of the 'initial founding team' to build Sponsored Ads from the ground up at Chewy!
What you'll do: - You will deploy machine learning and data-science to simplify shopping experience for pet-parents, to improve reach and discovery of new products of Chewy vendors and helping create an outcome where everybody wins ecosystem.
- Directly influence and collaborate with Product and Engineering leaders to evolve solutions using applied science to improve selection, ranking, relevance, deal-offerings, click through prediction models, dynamic bidding, and auction algorithms for Chewy advertising solutions.
- You will lead new models from ideation to experimentation, and eventually to production delivery to improve Chewy products offerings and advance applied science applications.
- Publish research papers in leading ML/AI/Advertising conferences solving problems for scale using innovative modelling.
- Establish high bar on model performance, establish applied-science implementation standard processes and mentoring junior scientists.
- Deploy solutions at Chewy scale improving overall customer engagement and value for Pet Parents.
- Formalizing proposals and communicating verbally and in writing to Chewy Senior Leadership and business customers with varying levels of technical knowledge, educating them about our research, as well as sharing insights and recommendations.
What You'll Need: - An advanced degree (M.S., PhD, or equivalent experience) in Operations Research, Statistics, Applied Mathematics, Data Science or related field or 5+ 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 pipeline, tuning, optimizing and evaluation.
- Experience with multiple techniques that include Predictive Models (Time Series and Regression), Linear Programming, and Classification, Search, Ranking or large-scale embeddings.
- Ability to translate sophisticated data sets and research into simple business recommendations.
Bonus: - Experience in e-commerce or retail.
- Experience with ML Services in AWS (SageMaker, Personalize) or equivalent.
Chewy is committed to equal opportunity. We value and embrace diversity and inclusion of all Team Members. If you have a disability under the Americans with Disabilities Act or similar law, and you need an accommodation during the application process or to perform these job requirements, or if you need a religious accommodation, please contact CAAR@chewy.com. If you have a question regarding your application, please contact HR@chewy.com. To access Chewy's Customer Privacy Policy, please click here. To access Chewy's California CPRA Job Applicant Privacy Policy, please click here.
Job Tags
Full time,