Applied Scientist - Economics and Causal Inference (m/f/d)

Recruiter
Zalando
Location
Berlin
Posted
22 Dec 2021
Closes
27 Jan 2022
Ref
3766065
Function
Operations
Level
Manager
As an Applied Scientist in our Economics Team at Zalando Lounge and Outlets, you will foster data-driven decision-making through the use of best-in-class causal inference methodologies, serving as in-house expert on causal identification and statistical modelling. You will drive business unit-wide research efforts, such as identifying key events in the customer journey that drive Customer Lifetime Value. Together with fellow economists on our team, you will represent our business unit in long-term company-wide research efforts that directly impact company strategy and product development.
WHERE YOUR EXPERTISE IS NEEDED
  • Utilize causal inference methods to answer business questions. For example, identifying key events that influence our long term relationships with our customers.
  • Design research plans and select the most appropriate methodologies.
  • Present your research to senior management and discuss its business implications.
  • Actively collaborate with economists and data science colleagues.
  • Act as an expert and consultant for analysts embedded in individual business teams wishing to employ quasi-experimental methods.
  • Keep the team up-to-date with the latest research in causal inference methods that rely on observational data.
  • Provide egoless constructive scientific feedback to peers and coach junior colleagues to become great researchers.
WHAT WE’RE LOOKING FOR
  • Ph.D. in Economics, Statistics, Epidemiology or similar social science fields with an emphasis on quantitative research methods. 2+ years of experience post-Ph.D.
  • Proven expertise in research design, hypothesis testing, and causal inference techniques as well as ability to think abstractly and discover patterns between problems, methodologies, and solutions.
  • Experience applying advanced causal identification research methods (experimental and/or quasi-experimental designs, e.g. matching, difference-in-differences).
  • Strong general scientific problem solving skills.
  • Highly proficient in R and/or Python and strong knowledge of SQL. Hands-on experience with Jupyter Notebooks, Apache Spark, Databricks, and Git is a plus.
  • As a self-starter, you drive results and have the ability to communicate relevant analytical insights from data to both technical and non-technical audiences.
PERKS AT WORK
  • A workplace run on trust, empowerment and feedback; positive, inspiring working atmosphere
  • Competitive salary, employee share shop, 40% Zalando shopping discount, discounts from external partners, centrally located offices, public transport discounts, municipality services, great IT equipment, flexible working times, additional holidays and volunteering time off, free beverages and fruits, diverse sports and health offerings
  • Mentoring and personal development opportunities and an international team of experts
  • Relocation assistance for internationals, PME family service and parent & child rooms

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, connecting customers, brands and partners across 23 markets. We drive digital solutions for fashion, logistics, advertising and research, bringing head-to-toe fashion to more than 45 million active customers through diverse skill-sets, interests and languages our teams choose to use.
ABOUT ZALANDO LOUNGE
Zalando Lounge is an online shopping club for fashion and lifestyle products in 13 European countries. We are the fastest growing sales channel of Zalando. In 2021 we grew by ca. 49%, breaching more than one billion EUR in yearly revenue for the first time. That's 14% of total Zalando Group revenue. Our rapid growth creates numerous research opportunities in diverse areas, such as customer experience, the use of various features and products, logistics and marketing.

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

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