Staff Scientist of Applied Machine Learning, Wayfair
Search
$207-230k
Office located in Mountain View, CA
A global online homeware marketplace
Open for applications
A global online homeware marketplace
1001+ employees
Open for applications
$207-230k
Office located in Mountain View, CA
1001+ employees
Company mission
To help everyone, anywhere create their feeling of home.
Role
Who you are
- 7+ years of industry experience in one or more of the following areas: Search, NLP, Ranking, Ads, Recommender Systems, and Machine Learning
- Strong technical skills with hands-on experience in Python and/or Java for solving ML problems, and familiarity with technical workflow tools for batch and real-time data processing
- Deep understanding of statistical and quantitative modeling techniques, including experimental design, statistical inference, hypothesis testing, and optimization
- Proven track record of executing large-scale ML projects, including the development of roadmaps and delivery of complex solutions
- Ability to effectively communicate complex technical concepts to both technical and non-technical stakeholders
- Experience with cloud-native technologies, particularly GCP and Vertex AI, is a plus
What the job involves
- The Search and Recommendations Machine Learning (ML) team is responsible for the algorithms driving Wayfair’s global search experience across all countries and stores, as well as all other recommendation services at Wayfair, including item-to-item, browse, email, and more
- These systems support both our core e-commerce experience and brand-based content, leveraging state-of-the-art web-scale ML, including advanced NLP, graph-based learning, and multi-modal technologies. Serving over 22 million active customers, our mission is to help customers quickly identify their style and needs, providing an end-to-end personalized and inspiring experience
- Design and develop cutting-edge multi-modal search and recommendation algorithms to enhance the customer shopping journey—from inspiration to purchase and delivery
- Implement scalable and reusable ML models for ranking systems (retrieval, relevance, and whole slate optimization) using a combination of large-scale customer behavioral data and a rich catalog of product information
- Collaborate closely with cross-functional teams, including data science, engineering, and product, to integrate ML solutions that drive measurable improvements in customer engagement and business outcomes
- Contribute to the evolution of diverse product experiences by developing scalable cloud-based solutions that can be applied across multiple business domains
- Explore and address complex marketplace challenges, such as supply and demand matching, product discovery, and cold-start problems, using innovative machine learning approaches
- Stay current with the latest research in machine learning and related fields, and actively contribute to the team's knowledge base by sharing insights and proposing novel solutions
Our take
Wayfair emerged in the early era of eCommerce with a mission to revolutionize online shopping, offering customers a convenient platform to purchase goods. Today, it stands as one of the foremost global players in the online furniture delivery industry, boasting an impressive inventory of over 33 million products.
Renowned for its extensive product range and comprehensive service offerings, Wayfair distinguishes itself by providing an end-to-end customer experience, from browsing to doorstep delivery. Despite its prominence, the company faces profitability challenges attributed largely to expansion expenses. Nonetheless, its solid presence in the competitive online homeware sector solidifies its position as a key contender.
With ambitious global expansion plans, Wayfair remains committed to maintaining its leadership in the industry. As it aspires to become the ultimate destination for all home needs, its more recent ventures into physical retail represent significant strides toward this overarching goal.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
Some candidates hear
back within 2 weeks
-14% employee growth in 12 months
Company
Company values
- Relentless Customer Focus: Delivering an exceptional customer experience drives everything we do. We invest in understanding our customers and partners. We are all in customer service
- Deliver Rsults With Agility: We prioritize work that drives long-term value. We execute with urgency, learn from failure, and nimbly pivot. The outcomes of our efforts are impactful, measurable results
- Use Good Judgement: We are bold and confident, never reckless. We make reasoned, calculated decisions based on data, critical thinking, and pattern recognition
- Build the Best Team: We lead by setting the bar high, articulating clear goals, and diving deep. We hire, develop, and leverage only the best. Our leaders continually reevaluate and strengthen their teams and do not shy away from hard decisions. We expect and demonstrate excellence
- Collaborate Effectively: We invest in cross-functional global partnerships that maximize impact and minimize duplication. We prize collaboration in all interactions – with our teammates, stakeholders, and suppliers. We disagree, align, and commit. Effectiveness and efficiency in collaboration are required.
- Respect Others: We earn and show respect, treating our teammates and partners with empathy and inclusion. We presume good intent while prioritizing impact. We balance confidence and candor with humility and kindness.
- Be an Owner: We are Wayfair first. We act on what’s best for the company, ahead of team or individual goals. We spend every dollar as if it is our own. We take pride in Wayfair’s success while planning the next win. We always think long-term
- Innovate & Improve: We are not limited by precedent. We boldly challenge the norm. We continually identify opportunities to innovate, improve, and simplify. We value incremental improvements, but we also look for game-changing breakthroughs.
- Adapt & Grow: We value adaptability and self-reflection. We find opportunity in every change, experience, and mistake. We are committed to continuous self-improvement.
Company HQ
Prudential / St. Botolph, Boston, MA
Articles
Leadership
Niraj Shah
(Co-Founder & CEO)Studied Engineering at Cornell University before co-founding Spinners, a Boston-based IT services company. Previously acted as Entrepreneur in Residence for Greylock and has served as CEO of Wayfair since co-founding the company in 2002.
Steven Conine
(Co-Founder)Co-founded Spinners before working for Operations at iXL. Conine also co-founded Pillar VC in 2016.
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