Data Science Tech Lead

San Francisco, CA

Applications have closed

Wayfair Inc.

Shop Wayfair for A Zillion Things Home across all styles and budgets. 5,000 brands of furniture, lighting, cookware, and more. Free Shipping on most items.

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By applying to this position, your application is automatically considered for the range of Data Science Tech Lead roles we have at Wayfair. If we think you might be a fit, a recruiter will reach out to learn more about your background and discuss relevant positions in more detail.

 

Who we are

Wayfair is moving the world so that anyone can live in a home they love – a journey enabled by more than 3,000 Wayfair engineers and a data-centric culture. Wayfair’s Data Science Marketing team builds algorithmic systems that drive our business, enhance customer experience, and improve customer loyalty. You will be part of a cross-functional, collaborative team driving development of world-class ML systems that improve our customer understanding and marketing decisions.

About the team: The Data Science Notifications Marketing team owns the ML modeling and strategy that powers marketing notification (Email, Push) send decisioning, answering questions like: should we send this notification to this customer? How frequently should we be sending notifications? At what time? Our goal is to build a scalable, ML-powered decision engine to continually optimize Wayfair’s dynamic marketing decisions for notifications, improving customer loyalty and driving revenue for the business. We work with stakeholders on the Marketing team, and partner Engineering teams (e.g., notification platform, notifications intelligence).

About the role: We are looking for a technical lead to join Wayfair’s Notifications Marketing team, to lead development of a Notifications Governance send decisioning layer, which will enable us to automate data-driven marketing send decisions within and across the Email and Push channels, ensuring our customers receive the best experience: “getting the right message to the right [customer] through the right channel at the right time with the right frequency.” The goal of Governance is to solve this problem by separating out the core model estimates (e.g., how likely is a customer to unsubscribe? How likely are they to click + order after getting a notification?) from the ultimate send decisions, and using an algorithmic approach to learn the optimal policy of sending/dropping notifications, in which the approach is (a) automated (minimizing resources/overhead of the current A/B testing and manual data collection, monitoring, analysis), (b) dynamic (continuing to explore/update the policy as the environment changes), (c) flexible (learning the best policy for each customer x notification type, i.e., interactions between customers/notification and policy), and (d) scalable (i.e., the approach can be scaled to capture batch and triggered decisions within and across channels, and eventually take into account the content of the notification (via Virgo “Content Understanding”)). We’re looking for someone to lead development of algorithms (e.g., contextual bandits) to govern these intra-/inter-channel notification send decisions, ultimately driving long-term customer value for the business.

What you’ll do

  • Own the development and expansion of multiple models, leveraging machine learning
  • Identify new opportunities and insights from the data (where can the models be improved? what is the projected ROI of a proposed modification?); continue to evolve models
  • Architect and build technical platforms for our algorithmic engines to run at scale
  • Work cross-functionally with Marketing and Engineering, and collaboratively with teammates
  • Leverage the knowledge of state-of-the-art methodology and industry best practices to raise the technical standard of the team and Wayfair Data Science community

What you’ll need

  • Minimum 4 years of industry experience in a data science or ML Engineering role or 3 years of industry experience with Ph.D. in a quantitative field (e.g., economics, physics, neuroscience)
  • Proficiency in Python
  • Solid experience building Machine Learning (ML) models, preferably also productionalizing models (e.g., Airflow)
  • Experience working with big data tools such as SQL, Spark, Hadoop, Hive, etc.
  • Strong written and verbal communication skills, ability to synthesize conclusions for non-experts, and desire to influence business decisions
  • A bias towards critical thinking, creatively solving problems from a customer-centric lens, and an intuitive sense for how the work aligns closely with business objectives
  • Intellectual curiosity and enthusiastic about continuous learning
  • Looking to make a big impact in a growing organization

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.

Tags: A/B testing Airflow Big Data Economics Engineering Hadoop Machine Learning Physics Python Spark SQL Testing

Perks/benefits: Career development Flex hours Flex vacation

Region: North America
Country: United States
Job stats:  1  0  0
Category: Leadership Jobs

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