Machine Learning Scientist II

Location: Mountain View, California

Team: Advertising MLS (Search & Recommendations)

Job Description

Wayfair's advertising team provides the core platforms and services that allow our suppliers to surface their products to the right customer to showcase their inventory and build their brand. We strive hard to make it a win-win-win for suppliers, Wayfair and customers by ranking relevant sponsored products that don’t hurt customer experience and by maintaining high ROAS for our advertisers. 

The Advertising team is searching for a Machine Learning Scientist II to work on the advertising ranking solutions. This team works on multi-objective optimizations which strike the balance of showing popular products and showcasing sponsored products or brand-aware display ads in the product search and recommendations. In this role, you’ll partner with fellow data scientists, engineers, analysts, and product managers to apply data science and machine learning skills to bring our next generation advertising platform to life.  

The ideal candidate enjoys sitting at the boundary of data science and engineering, and is comfortable working with partners across the organization to distill ambiguous business requirements into technical plans. This is an exciting opportunity to join a growing team with a tangible impact on the performance of Wayfair overall. You will directly impact and drive forward key business initiatives. Above all, you’ll get to work on problems that are both intellectually-challenging and drive real, measurable impact through our online A/B test platform. 

What You’ll Do 

• Develop quantitative models, leveraging machine learning and advanced data analysis techniques.
• Own the full Machine learning model life-cycle from conception to prototyping, testing, deploying, and measuring its overall business value.
• Coordinate, prepare, launch, and assess live experiments in order to measure the incremental impact of your own work and/or the work of partner teams.
• Uncover deep insights hidden in our vast repository of raw data, and provide tactical guidance on how to act on findings.
• Drive adoption & utilization of your products across the organization in ways that drive real business value.
• Architect and help define the required technical platforms that enable us to produce models at scale. 

What You'll Need

• PhD in a quantitative field (e.g. mathematics, economics, computer science, engineering, physics, neuroscience, operations research, etc.) and 4+ years of experience OR an advanced quantitative degree and at least 5+ years of experience.
• Ability to effectively partner with cross-functional leads: strong communication skills, ability to synthesize conclusions for non-technical partners, and a desire to influence business decisions.
• Ability to thrive in a dynamic environment where Data Science plays a key role in shaping business & technical priorities.
• Machine Learning experience in a professional or advanced academic setting (e.g., supervised/unsupervised learning, recommendation systems, reinforcement learning, deep learning, etc.)
• High comfort level with Python (preferred) or with other programming languages.
• Experience with advertising systems or multi objective optimization problems at a large scale is strongly preferred.
• Intellectual curiosity and a desire to always be learning!

Assistance for Individuals with Disabilities

Wayfair is fully committed to providing equal opportunities for all individuals, including individuals with disabilities. As part of this commitment, Wayfair will make reasonable accommodations to the known physical or mental limitations of qualified individuals with disabilities, unless doing so would impose an undue hardship on business operations. If you require a reasonable accommodation to participate in the job application or interview process, please let us know by completing our Accomodations for Applicants form.

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About Wayfair Inc.
Wayfair is one of the world’s largest online destinations for the home. Whether you work in our global headquarters in Boston or Berlin, or in our warehouses or offices throughout the world, we’re reinventing the way people shop for their homes. Through our commitment to industry-leading technology and creative problem-solving, we are confident that Wayfair will be home to the most rewarding wor