Senior Machine Learning Scientist, Wayfair
Supplier Advertising Science
Office located in Mountain View, CA
A global online homeware marketplace
Open for applications
A global online homeware marketplace
1001+ employees
Open for applications
Office located in Mountain View, CA
1001+ employees
Company mission
To help everyone, anywhere create their feeling of home.
Role
Who you are
- Advanced degree (Master or PhD) in Machine Learning, Computer Science, Engineering, Statistics, or a related quantitative field
- 3+ years (with PhD) or 5+ years (non-PhD) of experience in advanced machine learning and statistical modeling, including hands-on designing and building production models at scale
- Strong theoretical understanding and solid hands-on expertise deploying ML-based decision-making systems into production
- Familiarity with ML model development frameworks, ML orchestration and pipelines with experience in either Airflow, Kubeflow or MLFlow as well as Spark, Kubernetes, Docker, Python, and SQL
Desirable
- Experience in computational advertising, bidding algorithms, or search ranking
- Familiarity with Machine Learning platforms offered by Google Cloud and how to implement them on a large scale (e.g. BigQuery, GCS, Dataproc, AI Notebooks)
What the job involves
- You will be part of a cross-functional, collaborative team driving development of world-class ML systems that drive real-world impact
- We are looking for an experienced machine learning scientist to join the Supplier Advertising ML Science team
- In this role, you will be responsible for the development of our smart bidding platform (e.g. tROAS), targeting enhancements, smart campaigns, bid recommendations and other ML capabilities supporting our ads business
- You will work closely with other scientists, as well as members of our internal Product and Engineering teams, to apply your engineering and machine learning skills to solve some of our most impactful and intellectually challenging problems at Wayfair
- Provide technical leadership in the development of an automated and intelligent advertising system by advancing the state-of-the-art in machine learning techniques to support bidding and other optimizations
- Design, build, deploy and refine extensible, reusable, large-scale, and real-world platforms that optimize our ads experience
- Build robust monitoring, alerting, and edge-case handling mechanisms
- Collaborate closely and align with both our Ads and Search & Recommendations Product and Engineering partners to drive the integration of our smart bidding platform with the existing infrastructure and platforms at Wayfair
- Research new developments in advertising, sort and recommendations research and open-source packages, and incorporate them into our internal packages and systems
- Work cross-functionally with commercial stakeholders, engineers, analysts, and product managers to understand business problems or opportunities and develop appropriately scoped ML solutions
- Promote a culture of machine learning and ML science excellence by participating in weekly research, learning, and development sharing sessions
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
Insights
Many 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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