Working Student – Economist – Causal Inference (all genders)

THE ROLE & THE TEAM

In this role, you will delve into Zalando’s partners’ economic reality, gaining insights into our commissioning systems and utilizing our extensive dataset for high-exposure projects. Joining a cross-functional team that includes economists, strategists, and business experts, you will be responsible for selecting scientific approaches and building systems.

Your career growth will be nurtured through hands-on implementation of the latest ideas from the literature and rigorous A/B-tested evidence of your contributions. With access to Zalando’s comprehensive data sources, computational infrastructure, and software tooling, you’ll have the resources needed to thrive in a dynamic and innovative environment.

INCLUSIVE BY DESIGN

At Zalando, our vision is to be inclusive by design. And this vision starts with our hiring – we do not discriminate on the basis of gender identity, sexual orientation, personal expression, ethnicity, religious belief, or disability status. You are welcome to leave out your picture, age, or marital status from your application. We only assess candidates on their qualifications and merit. 

We want to provide you with a great candidate experience. Feel free to inform us of any accommodations you may need, so we can best support you throughout the hiring process. 

do.BETTER – our diversity & inclusion strategy: https://corporate.zalando.com/en/our-impact/dobetter-our-diversity-and-inclusion-strategy

Our employee resource groups: 

https://corporate.zalando.com/en/our-impact/our-employee-resource-groups 

WHAT WE’D LOVE YOU TO DO (AND LOVE DOING)

• Estimation: Help us reach the frontier of modeling Zalando Platform Dynamics: Building upon our existing and validated model of platform economics, we aim to more accurately and confidently estimate partner behavior, quantify the impact of strategic decisions on partners, and understand how actions and reactions impact Zalando customers.

• Experimentation: Assist us in building a system that leverages off-policy experimentation, automated causal learning, demand modeling, and continuous measurement to increase market efficiency and reduce waste.

• Entrepreneurship: We possess terabytes of observational and experimental data on purchase histories, clickstreams, and product similarity scores, among others. You will utilize these sources as needed and propose efficient experimentation strategies to generate interventional data where necessary.

• Evangelist of Scientific Methods: As an advocate of econometric methods, you will collaborate with economists and machine learning experts to develop the most data-efficient, impact-oriented solutions to enhance business processes.

WE’D LOVE TO MEET YOU IF

• You are studying bachelor/masters  in economics, or any discipline of STEM.

• You have a solid academic background in applying statistical methods in econometrics or computational economics (causal inference, numerical analysis, agent based modeling, stochastic modeling, game theory, experimentation).

• You already have the ability to implement your models in Python(Python Data Science Toolkit) and to handle terabytes of data using SQL and/or Spark on large, complex datasets.

• You are a team player, problem solving attitude and have a strong urge to learn and master new skills.

• You have a strong understanding of the platform economy and business KPIs to understand commercial health (Profitability Margin, EBIT Margin, Growth Rate etc) would be a big plus.

OUR OFFER

• The unique chance to be part of a market-leading company giving you the opportunity to learn and grow.

• A fast-moving and agile working environment where you’ll never face boredom.

• A highly motivated, international team with colleagues who will both inspire and support you.

• Training and further development opportunities to expand your skills and help you on your way.

• A corporate culture that allows you to make judgments based on your work results, not on the way you look – our motto: Every day is casual Friday.

• A 6 months contract as a part-time working student, starting asap.