The Marketing Data Science team at Wayfair develops machine learning models and reinforcement learning systems to power algorithmic decision-making across paid and owned media and marketing channels, including Paid Search, Display & Social Ads, Direct Mail, Email Marketing and Push Notifications.
In this role, you will leverage massive amounts of data to solve complex business problems focused on enhancing the customer experience and driving long-term value. You will be processing petabytes of first party and third party clickstream data to build customer-centric ML models. These models ultimately plug into our ecosystem of algorithmic decision-optimization systems and power millions customer-level decisions each day. Depending on your specific pod, these predictions or decisions could range from: What do we think she needs? Whats her stylistic preference? Should we show her an ad? On what channels? How frequently? How much do we bid? Which creative asset speaks to her uniqueness? etc.
Above all, youll get to work on problems that are both intellectually-challenging and drive real, measurable impact, first and foremost, for our customers - and as a result for Wayfair at large. To get a better sense of the type of projects we work on, check out our Data Science & Machine Learning blog posts here!
What You'll Do
- Partner closely with peer data scientists and ML engineers to build highly scalable modeling approaches and deploy model outputs into existing production systems.
- Train deep-learning models for representation learning, capturing what makes customers unique and enhancing customer-level personalization.
- Wrangle and process petabytes of data from various data sources.
- Youll be a builder of tools, software, and microservices that enhance or streamline various steps or challenges within the data science workflow & our tech stack.
- Be obsessed with the customer and maintain a customer-centric lens in how we frame, approach, and ultimately solve every problem we work on.
What You'll Need
- BSc in computer science and 4+ years of experience in data engineering, data science,or software development, or PhD or MS in computer science and 3+ years experience in data engineering, data science,or software development
- Proficient in parallel computing and big data technologies, particularly Hadoop, Hive, Spark.
- Commercial experience training and productionizing deep learning models, and in production-environment-driven ML design.
- Proficient at one or more programming languages, e.g. Python, R, Java, C++, etc.
- Comfortable with SQL and ability to wrangle data from various sources
- Action-oriented, autonomous individual with a bias towards solving problems from a customer-centric lens
- A knack for finding the right degree of pragmatism and delivering solutions in a iterative manner, adding only as much complexity as needed in each step along the way
- A curious mind open to continuous learning and motivated to autonomously drive projects and thrive in a dynamic environment where there can be ambiguity
About Wayfair Inc.
Wayfair is one of the worlds 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, were 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 youre looking for rapid growth, constant learning, and dynamic challenges, then youll find that amazing career opportunities are knocking.
No matter who you are, Wayfair is a place you can call home. Were 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. Thats why were 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.