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Associate Director, Data Science Paid Search
The Data Science Marketing team at Wayfair develops machine-learned models and algorithms to drive business impact across a multitude of marketing channels; Paid Search, Display & Social Ads, Direct Mail, Email Marketing and Push Notifications to name a few. We partner closely with our Marketing and Engineering counterparts in order to create opportunities and uncover new efficiencies and channels to reach a wide range of customers.
The Data Science Marketing team is looking for a Head of Paid Search to jointly manage and co-develop our next generation of Paid Search bidding platform along with our internal Marketing and Engineering teams.
What You'll Do
- Responsible for the data science components of our Paid Search platform which makes up the one of the biggest marketing channels for Wayfair
- Work towards scaling up already large base of tens of millions of keywords and SKUs being bid on a daily and weekly basis
- Own the full Data Science life-cycle from conception to prototyping, testing, deploying, and measuring its overall business value
- Develop quantitative models, leveraging machine learning and advanced data analysis techniques
- Architect and build technical platforms for our algorithmic engines to run at scale
- Leverage our work in order to increase adoption across our business partners, to drive real business value
- Uncover deep insight hidden in our vast repository of raw data, and provide tactical guidance on how act on findings
- Use data to improve the decision-making of our employees, and ultimately, to enhance the experience of our customers and our suppliers
- Strong partnership with business and engineering teams
- Provide technical leadership and strategic initiatives for your team
- Deliver presentations to high level business stakeholders that tell cohesive, logical stories using data
What You'll Need
- 5+ years of experience leading high performing and hands-on teams and managing stakeholder relationships
- 5+ years of experience in a quantitative or technical work environment or advanced degree (PhD) in quantitative field (e.g. mathematics, economics, computer science, engineering, physics, neuroscience, operations research etc.)
- Intuitive sense of how quantitative and technical work aligns closely with business priorities and business value
- Ability to effectively work with business leads: strong communication skills, ability to synthesize conclusions for non-experts and desire to influence business decisions
- High comfort level with programming, e.g. languages such as Python, R, Scala, Java, C++, C#, etc
- Machine Learning experience (such as supervised/unsupervised learning, recommendation systems, reinforcement learning, deep learning, etc.)
- Ability to thrive in a dynamic environment where there can be degrees of ambiguity
- Bonus points for intellectual curiosity and a strong desire to always be learning
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.
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