Senior Tech Lead - Data Science Marketing

Senior Tech Lead - Data Science Marketing

Boston, MA 

Who We Are

At Wayfair, data drives all of our business decisions. The Marketing Data Science team develops supervised, unsupervised, and reinforcement learning systems to power algorithmic decision-making across paid and owned media and marketing channels, including Display & Social Ads, Video, Direct Mail, Email Marketing, and Push Notifications, etc. These channels drive millions of site visits and billions of dollars of GRS to our business.

We are looking for a senior technical lead to join the Data Science Marketing team. You will lead the development and integration of online and batch learning DS systems to drive ad tech innovation at Wayfair and optimize our omni-channel marketing decisions. You will interact with team leads across Marketing, Ad Tech, Infrastructure, and other Data Science and Engineering orgs, to solve important business problems at Wayfair. Above all, you’ll get to work on problems that are intellectually challenging and highly impactful for both Wayfair and our customers. To get a better sense of the type of projects we actually work on, check out our Data Science & Machine Learning blog posts here!

What You'll Do

• Lead a strong-performing team of data scientists and ML engineers to build scalable ML systems with a focused scope for improving paid media marketing decisions
• Responsible for the full data science life-cycle from conception to prototyping, testing, deploying, and measuring its overall business value
• Architect and build technical platforms for our algorithmic engines to run at scale
• Use data to improve how we make decisions and ultimately, enhance customer experience and drive loyalty
• Uncover deep insight hidden in our vast repository of raw data, and provide tactical guidance on how to act on findings
• Leverage our work in order to increase adoption across our business partners, to drive real business value
• Strong partnership with business and engineering teams
• Deliver presentations to high level business stakeholders that tell cohesive, logical stories using data

What You'll Need

• 4+ years of experience working as a professional data scientist, ML engineer, or software developer
• Experience in coaching, mentoring, and developing a data science or engineering team
• Proficient in one or more programming language, e.g. Python, R, Java, C++, etc.
• Prior experience building scalable data processing pipelines with big data tools such as Hadoop, Hive, SQL, Spark, etc.
• Experience with GCP, Airflow, and containerization (Docker) are nice to have
• Strong communication skills; ability to work with business leads and effectively articulate tech requirements to non-experts; desire to influence business decisions and improve Wayfair with technology
• Experience in Bayesian Learning, Multi-armed Bandits, or Reinforcement Learning is strongly preferred

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.