Director, Data Science and Machine Learning
The Data Science & Machine Learning team (DS & ML) at Wayfair builds algorithms that support some of our most impactful business areas: Marketing, Catalog, Sales & Service, Supply Chain and more. Our teams of data scientists embed with engineering and business teams to develop and deliver algorithms that improve the experiences of our customers and suppliers and that help enable other teams within the company. Our blog highlights many of the projects that we are working on across the full team.
We have grown an innovative group of data scientists based in our Boston office. Their primary focuses are: (1) Building customer scoring and marketing algorithms to help drive our marketing and personalization programs (2) Developing a scalable and quantitative understanding of our product catalog via meta-tagging and deep-learning based embeddings (3) Building scalable platforms to support measurement throughout Wayfair LLC (4) Working with our Sales and Service functions to create algorithm-driven decision support tooling to improve their efficacy. They have a global mandate for the products that they develop and we are excited about the potential of continued investment in these workstreams in 2021 and beyond.
We are seeking a Boston-based Engineering Director who will report into the head of DS & ML with the overall responsibility to up-level our machine learning engineering capability in our Boston office - our two year goal is to significantly increase the delivery velocity of our DS & ML teams and this hire will be key to achieving this goal.
In this position, you will have exposure to a broad range of machine learning projects. You will develop & execute the strategy to empower our data science teams to improve speed-to-production, impact and scalability. Your team will operationalize and own a broad range of machine learning models that will impact the business at scale. We expect this leader to drive these changes through a mix of: (1) leading sprint teams of machine learning engineers to directly drive and own operationalization (2) up-leveling existing data scientists (3) working with Wayfair’s platforms & infrastructure teams to drive adoption of new technology in the machine learning space and more.
What You’ll Do
- Create & execute machine learning engineering roadmap
- Hire & develop a world class and diverse team of machine learning engineers who partner with data science teams to operationalize dozens of machine learning models
- Serve as a senior subject matter expert on machine learning technology at scale
- Increase the rate of delivery of the DS & ML group through stronger engineering practices and best-in-class technology
- Partner with a wide range off leaders with our DS & ML group, as well as Engineering more broadly
- Explore the latest machine learning technologies that support the team’s overall mission (in particular, in the NLP and deep learning spaces)
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 work of your career. If you’re looking for rapid growth, constant learning, and dynamic challenges, then you’ll find that amazing career opportunities are knocking.
No matter who you are, Wayfair is a place you can call home. We’re a community of innovators, risk-takers, and trailblazers who celebrate our differences, and know that our unique perspectives make us stronger, smarter, and well-positioned for success. We value and rely on the collective voices of our employees, customers, community, and suppliers to help guide us as we build a better Wayfair – and world – for all. Every voice, every perspective matters. That’s why we’re proud to be an equal opportunity employer. We do not discriminate on the basis of race, color, ethnicity, ancestry, religion, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, or genetic information.