Original Beschreibung
# Senior Applied Scientist - Assortment Insights (all genders)
**Zurich** | **Full time**
**THE ROLE AND THE TEAM**
The Economics group at Zalando is seeking a Senior Applied Scientist (Economist) position to help launch a newly founded Assortment Insights team in Zurich, Switzerland. This team is tasked with delivering reliable and actionable business insights about our assortment for a wide range of business decision processes across the company. The questions addressed will include, (1) What is relevant assortment for our customers and how does that vary by market, by product category, by customer type, and more?, (2) How exactly do we map those insights into the business decisions our teams must make?, (3) How do we generate such insights at scale?, and many more!
As a Senior Applied Scientist, you will need to rely on a wide range of scientific, organizational, and personal skills. The two primary areas of scientific expertise we will use are experimentation and tools from "Industrial Organization" economics, so a strong background in statistics and experimentation, the economics of consumer demand, firm decision-making, and competition, and structural modeling and estimation are all essential. Familiarity with and some experience using observational causal inference and machine learning methods would also be valuable. Interest and experience with mapping business needs to scientific problems and finding solutions in ambiguous problem spaces is also essential, as well as working pragmatically with colleagues from a wide variety of backgrounds to find feasible workable solutions that will yield reliable and actionable insights.
This role will be attractive to candidates seeking to make an impact on a collection of critical business problems for Zalando and grow their career while doing so. The problem space here is ambiguous, so the ideal candidate will be intellectually curious, entrepreneurial, and experienced with a range of applied science methods. They will join the team "on the ground floor," with all the benefits and costs that implies (broad scope, ability to have significant impact on the one side; problem space ambiguity, yet-to-be-defined approaches and processes on the other). Core skills in statistics and experimentation are required, as are skills in Industrial Organization economics (i.e. consumer demand, competition economics, structural modeling and estimation). Familiarity with the retail e-commerce and/or fashion sectors and excellent communication skills are both a plus and experience addressing business problems related to assortment is a strong plus.
****WHERE YOUR EXPERTISE IS NEEDED****
* Bringing a range of applied science expertise to help support and, as relevant, drive the research agenda in an exciting new domain (Assortment Insights).
* Supporting robust evidence-based decision-making by conducting high-quality scientific research and scaling the insights from that research into production,
* Making such insights accessible and easy to use for our stakeholders and customers,
* Educating a diverse range of stakeholders, at all levels, on how to use the right tool for the right use case, and
* Leading and owning processes that help the company keep a high bar in terms of decision-making and reasoning around insights.
****WHAT WE ARE LOOKING FOR****
* A PhD in Economics (inc. Econometrics), Statistics, or related field with at least 2 years of industry experience in applied Economics and Statistics/Experimentation.
* Expertise in the first two areas below, with the next two not required but a plus:
* Statistics/Experimentation, including 2+ of advanced experiment designs, variance reduction methods, trigger/dilution methods, surrogate methods, experimentation at scale
* "Industrial Organization" economics, including the economics of consumer demand, firm decision-making, and competition, as well as structural modeling and estimation
* Observational causal inference/Econometrics, including DiD, synthetic controls, Double ML/Causal data science, and heterogeneous treatment effects estimation at scale
* Machine learning methods
* Experience building and leading applied science/insights products: from the problem definition to data selection and model development to deployment in production.
* A deep understanding of the theory behind the state-of-the-art methods in your primary domain(s) as well as a broad overview of best practices in your field
* An intuition for data: extensive experience of working with large online datasets, ability as well as to identify the appropriate statistical modeling assumptions and approaches that "let the data tell its story"
* Coding skills in Python and/or R as well as experience with common big data processing and manipulation tools such as Spark and SQL
* Nice to have: experience with Cloud Computing frameworks (e.g., AWS), other programming languages such as Scala