Machine Learning Science Graduate Intern - Summer 2024

Wayfair

Sep 25, 2023

Applications are closed

Internship
Full-time
Summer Internship
Software Engineering
Boston

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Requirements

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.
Preferred Qualifications:
An affinity for data along with experience leveraging statistics and regression analysis
Intuitive sense of how quantitative and technical work aligns closely with business priorities and business value
Experience with programming skills relevant to data science such as Python and R. Very big plus for High comfort level with languages and tools such as Python, Pytorch/TF, github, pyspark, Docker, SQL, GCP.
Familiarity with data structures, algorithms, OOP, and programming in a team environment
Quick learner with an analytical approach to solving problems as part of a team who has strong communication skills
Ability to thrive in a dynamic environment where there can be degrees of ambiguity
Ability to effectively work with technical leads: ability to synthesize conclusions for non-experts and desire to influence technical decisions

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

Wayfair

Retail & Consumer Goods

Industry

10,001+

Employees

2002

Founded Year

Mission & Purpose

Wayfair is the destination for all things home: helping everyone, anywhere create their feeling of home. From expert customer service to the development of tools that make the shopping process easier, to carry one of the widest and deepest selections of items for every space, style, and budget, Wayfair gives everyone the power to create spaces that are just right for them.

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