Machine Learning Science Graduate Intern - Summer 2024

Program Dates: June 3, 2024 - August 9, 2024

Wayfair is seeking analytical and action-oriented candidates for the Machine Learning Science intern opportunities starting in June 2024. The Machine Learning team builds the algorithmic systems that drive our business. With 11 expansive workstreams (Search, Pricing, Personalization & Recommendations, Merchandising, Marketing, Measurement, B2B, Computer Vision, Sales, Services, and Supply Chain ), and more than 20 specialized sub-teams, the projects that our teams work on directly impact our customers on a massive scale. Our internship program is a 10-week full-time position that will give you the opportunity of exploring core Wayfair business challenges and coming up with state-of-the-art solutions and taking them into production. You will work with great mentors who will help you all the way from defining the problem and identifying the potential solutions to planning the path to take it to product and potentially publishing your work in reputed AI/ML/DS venues. 

Who We Are | Machine Learning Science at Wayfair

We work closely with stakeholders across the business to build scalable ML solutions and algorithmic platforms that drive incremental revenue, enhance the customer experience, & improve customer loyalty. The projects that our teams work on are driven from the ground up – we look for entrepreneurial individuals who want to take ownership over their own agenda and thrive in a collaborative team environment. Take for example (1) Developing novel machine learning models to identify latent customer preferences so that the best products can be highlighted in real-time to our customers, (2) Optimizing profitability and business strategy by accurately forecasting future demand, costs and margin; Estimating the long-term impacts on customer behavior of short-term actions via experimentation, or (3) Creating machine learning solutions to detect product duplicates across the millions of products in our catalog and scaling the solution to handle real-time uploads of new products by partners. Data is at the heart of everything we do and there is very little at Wayfair that our Machine Learning team does not touch. They work closely with various teams across the business to build and scale novel solutions to business problems via machine learning. With an in-house A/B testing platform and rolling code deployments, our team can quickly and clearly see the impact that its work has on the company at large and the algorithms you create will directly impact the customer’s experience.

What You'll Do | Responsibilities

• Own the full Data Science/Machine Learning lifecycle from conception to prototyping, testing, deploying, and measuring its overall business value
• Develop and scale state-of-the-art machine learning methods and quantitative models to address core business problems
• Integrate your algorithmic solutions into our technical platforms to run at scale and directly change the experiences of customers on our site
• Drive measurable business value collaborating with business teams to change the course of Wayfair
• Pilot projects using new open source tools and packages to enable novel machine learning techniques across the company
• Uncover deep insights hidden in our vast repository of raw data and provide tactical guidance on how to act on findings
• Use data to improve the decision-making of our employees, and ultimately, to enhance the experience of our customers and our suppliers
• Work with a team of friendly and motivated scientists working together to build novel solutions to business problems
• Collaborate with ML Scientists and software engineers to create maintainable, scalable and debuggable code by bringing strong software development practices
• Drive any potential scientific publications based on the results in major Data Science and Machine Learning conferences or workshops

Bonus: You will learn a ton and have fun!

What You'll Need | Qualifications

 

Basic Qualifications:

• Currently enrolled in a PhD degree program, or a Masters degree program with at least 3 years of relevant full-time work experience, in a quantitative field (Mathematics, Science, Engineering, Computer Science, Statistics/Biostatistics, Economics, etc.), with a graduation date between spring - summer 2025.
• Must be returning to the course of study following completion of the internship.
• Proficient knowledge of structured programming language(s) (e.g. Python, R)
• Some familiarity with regression and machine learning techniques, such as supervised/unsupervised learning, recommendation systems, reinforcement learning, deep learning, etc

 

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