Machine Learning Scientist I

Salary Range: $132,500 - $150,700 per year

Location: Toronto, ON

This is a Toronto based opportunity with a 3 day in office expectation (Tuesday - Thursday) with 2 days remote (Monday and Friday).

Wayfair is continuing to expand our commitment to hiring and supporting talent early in their careers, focusing on filling opportunities with recent graduates who have 0-3 years of work experience. We are continually recruiting candidates for this position on a rolling basis as we have a high volume of openings that become available.

Who We Are

Wayfair is on a mission to find the most talented engineers entering the tech world Do you love innovating and creating new tools from scratch? We’re looking for engineers who love Wayfair is looking for candidates who are passionate about programming, and have strong core fundamentals. If you feel confident in your knowledge of object oriented design, data structures, & algorithms and your ability to grow your skills over time. We want to connect with developers who are eager to work in a highly collaborative team and add to Wayfair’s culture. You will have the opportunity to work on one of the following teams:sharing ideas, collaborating to improve them, and being a part of the full software development process. Our engineers are enthusiastic problem solvers and our teams are highly collaborative.

What You’ll Do

• 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

What You’ll Need

Basic Qualifications

• 1-3 years of transferable experience in a corporate environment, including internship and co-op experience
• Master’s degree in a quantitative field (Mathematics, Science, Engineering, Computer Science, Statistics/Biostatistics, Economics, Physics, Robotics, Operations Research, etc.) or Bachelor's degree in a quantitative field + 1+ years of experience
• Proficient knowledge of structured programming language(s) (e.g. Python)
• Experience with languages and tools relevant to data science, including Pytorch/TF, Github,Pyspark, Docker, SQL, GCP
• Excellent communication skills, with the ability to clearly articulate complex AI concepts to non-technical stakeholders while collaborating across teams
• Demonstrated ability to quickly learn new tools and techniques in a fast-paced, evolving environment, while managing multiple priorities with a high level of attention to detail and staying current with the latest ML research

Preferred Qualifications

• Familiarity with regression and machine learning techniques, such as supervised/unsupervised learning, recommendation systems, reinforcement learning, deep learning, etc.
• 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
• 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 decision
• Hands-on experience with large language models (e.g., GPT, BERT, Transformers) and Retrieval-Augmented Generation (RAG) techniques, and fine-tuning LLM models to address specific business c