Data Science Tech Lead – Push Notifications 730 views

Who They Are

Wayfair’s Data Science team builds the algorithmic systems that drive their 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, etc.

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

They are looking for a technical lead to join the Data Science Marketing team, with an emphasis on developing scalable algorithms and platforms to power Wayfair’s customer communication marketing channels including Email, App Push Notifications, etc. Customer communication channels drive millions of site visits and billions of dollars of GRS to their business. You will be working together with other data scientists, as well as multiple marketing and engineering teams to solve one of their most impactful and intellectually challenging data science problems at Wayfair. 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.

What You’ll Do

• 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 their 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 (Ph.D.) in a 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.)
• 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 effectively work with business leads: strong communication skills, ability to synthesize conclusions for non-experts, and desire to influence business decisions