Economist II

Join our Pricing team and play a crucial role in shaping Wayfair's pricing strategy! We're a science team with a mission to optimize long-term profitability by finding the perfect balance between short-term profitability and sustainable customer growth. We do this by leveraging economic theory, cutting-edge ML, econometrics, and live experimentation to ensure our pricing is competitive, fair to our suppliers, and drives customer engagement.

In this role, you'll be pushing the boundaries of demand estimation and causal inference by working with rich, high-volume customer data and ML tools. You'll use both observational and experimental methods to understand how customer short- and long-term price sensitivity shifts in response to various business decisions. Partnering with our engineering team, you'll implement these best-in-class approaches as scalable solutions that drive impact by improving Wayfair pricing strategies. 

What you’ll do

• Lead R&D effort to develop innovative demand estimation approaches that will extend current capabilities and develop new ML products to power our pricing.
• Understand our pricing strategy and optimization algorithm to identify what to measure and how to measure it.
• Work highly cross-functionally with business leadership, stakeholders, and partner science and engineering teams to drive the integration of model outputs into company-wide business decision-making and existing production systems. 
• Developing robust solutions to infer or recover causal relationships from observational data, in a way that minimizes self-selection or third-variable problems and reliance on experimental data. 
• Develop and own communication strategy for both technical and business stakeholders (including executive documentation and progress updates)
• Act as a subject matter expert and thought leader on demand estimation and causal inference techniques 
• To stay ahead of the curve, you'll continuously research and evaluate new techniques in data science, machine learning, and pricing optimization.

Who you are

• PhD in Economics, Statistics or other quantitative field with an emphasis on causal inference and/or structural modeling (e.g. industrial organization, structural labor, quantitative marketing, OR).
• 2 years of experience working as a professional ML or research scientist in causal inference. Consistent track record of autonomous delivery of DS/ML projects that drive measurable business impact. 
• Collaborative team player who wants to see themselves and others thrive. 
• Expertise in causal inference and interest in bringing best-in-class solutions to e-commerce space. 
• Takes a customer-centric approach to ideation and problem-solving
• Track-record of influencing non-technical stakeholders on strategic direction by leveraging data-driven insights; excellent written and verbal communication.
• Strategic thinker with a customer-centric mindset and a desire for creative problem solving, looking to make a big impact in a growing organization
• Strong SQL skills and excellent software engineering skills in Python
• Nice-to-haves:
• Experience with GCP (BigQuery, GCS, Dataproc, Notebooks), Airflow, and containerization (Docker)
• Experience building scalable data processing pipelines with big data tools such as Hadoop, Hive, Spark, etc.

Massachusetts Applicants: I understand that it is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.