Manager Causal Data Science (Pricing Experimentation)

Pricing is a key lever to steer Zalando's ₠10+bn in GMV, and to improve our platform economics. Better pricing has significant economic impact, but through managing our seasonal inventory it also reduces waste and our environmental footprint. Here, we make a real difference with advanced econometric and causal analysis. We are looking for a data science manager to build an ambitious research roadmap while delivering tangible results to our core business metrics.

As the manager of our Pricing Measurement team, you and your team are directly responsible for incremental and counterfactual estimates of market reactions to Zalando's pricing decisions. You achieve this by careful causal modeling of observational data, and by providing the expertise, tooling, and operations for experimentation in the form of complex A/B tests as well as off-policy exploration.

We are building a new generation of business steering tools to allow return-on-investment (ROI) tradeoffs between pricing, marketing, and supply. Your role is to support this by being the technical and people lead for pricing ROI measurement. Through this role, you will learn about our holistic pricing system, and interact with stakeholders across the entire pricing platform.

You will directly manage 5-8 data scientists, economists, and engineers. You will be part of a cross-functional team, responsible for building the tools and scientific approaches for experimentation and inference. You will report to the Head of Applied Science, and receive both technical and managerial support and mentorship where needed.

WHERE YOUR EXPERTISE IS NEEDED

• Lead an interdisciplinary delivery team of data scientists, economists, and engineers; liaise closely with product managers, to whom you are a trusted sounding board and translator between commercial needs and scientific possibilities.
• Define a research roadmap and communicate with your leadership peers to integrate measurement solutions into the entirety of our pricing platform. Help shape our vision for continuous learning and closed-loop experimentation.
• Design an effective team that raises the bar on scientifically robust measurement that is trusted and referenced across the pricing organization and beyond. Recruit the right candidates for your mission.
• Manage high-performing PhD-level scientists, providing technical guidance and career development.

WHAT WE'RE LOOKING FOR

• Excellent educational background (PhD, or M.Sc. with relevant professional experience) in economics, computer science, psychology, political science, statistics or other similar quantitative fields.
• Scientific pragmatism: good judgement for the right level of rigor to deliver results.
• First leadership experience, including responsibility for your team's career development, for example through mentoring.
• Sufficient technical skills in SQL and python or R to provide credible support to your team. Ideally some experience with causal inference and/or pricing.
• Passion for data, leadership, and tangible business impact.

We celebrate diversity and are committed to building teams that represent a variety of backgrounds, perspectives and skills. All employment is decided on the basis of qualifications, merit and business need.

ABOUT ZALANDO

Zalando is Europe's leading online platform for fashion and lifestyle, connecting customers, brands, and partners across 17 markets. We drive digital solutions for fashion, logistics, advertising, and research, bringing head-to-toe fashion to more than 23 million active customers through diverse skill-sets, interests, and languages our teams choose to use.

Pricing Platform is at the core of our commercial operation. Our tools help to determine how much of each product to buy, to recommend the best prices for these products, and to ensure that we have the right level of logistics capacity to fulfill our customers' demand. The Pricing Platform engineering team uses cutting-edge technology, data science, and machine learning, to forecast demand and pricing with a focus on business and customer experience. Partnerships happen with all key engineering and product teams, business and customer experience teams.

Please note that all applications must be completed using the online form - we do not accept applications via e-mail.