Machine Learning Scientist, Wayfair
Global Supplier Tech
A global online homeware marketplace
Job no longer available
A global online homeware marketplace
1001+ employees
Job no longer available
1001+ employees
Company mission
To help everyone, anywhere create their feeling of home.
Role
Who you are
- Advanced degree (PhD) in a quantitative field (e.g. mathematics, economics, computer science, engineering, physics, neuroscience, operations research, etc.) or 1-2 years of experience with a Masters in a quantitative field or 4+ years of experience with a Bachelors in a quantitative field
- Machine Learning using a wide range of techniques (such as supervised/weakly supervised learning, computer vision, deep learning, etc.)
- Proficient at one or more programming languages, e.g. Python, Java, C++, etc
- Experience building scalable data processing pipelines with big data tools such as Hadoop, Hive, SQL, Spark, etc
- Experience with cloud compute (i.e. GCP, AWS), schedulers (i.e. Airflow), and containerization (Docker) are nice to have
- Ability to effectively work with business leads: strong communication skills, ability to synthesize conclusions for non-experts and desire to influence business decisions
- A bias towards solving problems and an intuitive sense for how the work aligns closely with business objectives
- Ability to thrive in a dynamic environment where there can be varying levels of ambiguity
What the job involves
- Wayfair’s Machine Learning team builds the algorithmic systems that drive our business, enhance customer experience, & improve customer loyalty
- This ML team develops advanced machine learning and econometric models to power a range of high value initiatives for Wayfair
- Deep catalog understanding to power tagging, comparisons of products and identification of high potential products in our catalog
- Drive pricing and profitability for all of Wayfair
- Drive efficiencies and improve outcomes across the Wayfair’s B2B and Sales programs
- We are looking for an ML scientist to join the Global Supplier Tech Science and Analytics team, with an emphasis on developing scalable algorithms and platforms to better serve Wayfair’s customers
- You will need to own the design, prototyping, implementation and governance of ML models
- You will be working together with other data scientists, as well as multiple business and engineering teams to solve some of the most impactful and intellectually challenging data science and machine learning problems at Wayfair
- Develop sophisticated and cutting-edge Machine Learning models using Wayfair’s product and customer data to power a wide range of company initiatives
- Integrate model outputs into a variety of end use cases with partner business and engineering teams to drive value for Wayfair
- Work with partner engineering teams to build real-time models & services for widespread consumption across Wayfair
- Stay up-to-date on the latest ML research and appropriately utilize state-of the-art techniques in delivering solutions
- Drive the development, implementation, testing and governance of ML solutions
- Communicate results and influence decision making with senior stakeholders to drive improvements in end-to-end processes
Our take
Wayfair emerged in the early era of eCommerce with a mission to revolutionise 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
-14% employee growth in 12 months
Company
Company HQ
Prudential / St. Botolph, Boston, MA
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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