Head of Pricing & Forecasting Science, Global Supplier Technology

The salary range for this position is $216,000 - $228,000. Base pay offered may vary depending on location, job-related knowledge, skills, and experience. Restricted stock units may be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits, dependent on the position offered. 

Who We Are:
The Pricing, Profitability, and Demand Forecasting group is a team of approximately 20 full-time economists and ML scientists. We are a collaborative and lively scientific community working at the core of Wayfair's commercial strategy. Our team partners closely with engineering, data science, product, and commercial leaders to solve complex challenges and shape the company's future through the strategic application of science. As the leader of this group, you will be central to this mission, guiding the teams that drive our technical and business impact.

What You’ll Do:

• Lead the technical strategy for the pricing, profitability, and forecasting organization to solve large, complex problems in measurement, prediction, optimization, and forecasting.
• Design and build scalable solutions that ensure system interoperability and scientific rigor.
• Integrate underlying models into a unified technology platform that supports stakeholders with diverse needs, helping them reach sound causal conclusions.
• Grow and develop a high performing science team, by mentoring and providing guidance to junior team members to enhance their skills.
• Collaborate with leaders in engineering, product management, data science, and business leadership to address complex problems holistically.
• Influence company-wide strategic decisions in the pricing space by translating complex ideas for non-technical audiences.

We’re Excited About You Because You Have:

• PhD in quantitative fields (Economics, Quantitative Marketing, Statistics, Computer Science, Operations Research, etc.).
• 7+ years of industry experience in one or more of the following: observational causal inference, experimentation, or building and maintaining large-scale measurement systems.
• 2+ years of industry experience managing individual contributors as well as managers in a high performing science organization.
• Proficient coding skills: advanced experience in Python for machine learning and causal inference, along with familiarity with workflow tools (e.g., Airflow, Composer) for batch and real-time processes and cloud-native technologies.
• A proven track record of delivering large-scale technical projects with significant business impact.
• The ability to work closely with senior business stakeholders, translate complex ideas for non-experts, and influence strategic decisions at the Director+ level.

Nice to have:

• Experience in building optimization algorithms powered by causal inference system in price, marketing, or ads,
• Experience in scaling causal inference models that blend observational and experimental data.
• Familiarity with GCP and Vertex AI.