: Data Science Manager - Marketing

Who We Are

Wayfairs Data Science team builds the algorithmic systems that drive our business, enhance customer experience, & improve customer loyalty. 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.

We partner closely with our Marketing, Ad Tech, and Engineering to build scalable algorithmic systems responsible for optimizing millions of customer-level decisions each day: Who do we target? On what channels? How frequently? How much do we bid? What type of ad do we show? Which creative asset? etc.

We are looking for a Senior Data Science Manager to join the Data Science Marketing team working on our algorithmic marketing platform, with an emphasis on developing scalable Reinforcement Learning algorithms and/or constrained optimization problems. You will be processing petabytes of first party and third party clickstream data to build customer-centric ML models and power high-frequency, customer-level, decision-making systems. This role will be highly cross-functional and working across paid and owned media. When you think about the large number of interrelated decisions our algorithmic system is responsible for, it becomes clear why this is one of our most impactful but also intellectually challenging data science problems at Wayfair. Our algorithms optimize millions of real-time decisions, and we power over $800M worth of advertising spend across the portfolio of channels we support.

What You'll Do

  • Responsible for 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 to act on findings
  • Use data to improve how we make decisions and ultimately, enhance customer experience and drive loyalty
  • 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 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.)
    Machine Learning experience (such as supervised/unsupervised learning, recommendation systems, reinforcement learning, deep learning, etc.)
  • Bayesian Learning, Multi-armed Bandits, or Reinforcement Learning strongly preferred
  • Ability to effectively work with business leads: strong communication skills, ability to synthesize conclusions for non-experts and desire to influence business decisions
  • Proficient at one or more programming languages, 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
  • A bias towards solving problems from a customer-centric lens and an intuitive sense for how the work aligns closely with business objectives
  • Ability to thrive in a dynamic environment where there can be degrees of ambiguity
  • Ability to effectively work with business leads: strong communication skills, ability to synthesize conclusions for non-experts and desire to influence business decisions