Alles Klar: Research Related Roles at Zalando

Zalando VP Search & Personalization, Reiner Kraft on how research roles are organized at Zalando.

In the past three years we’ve made a lot of progress re-organizing research and development in Zalando. Each role has a clear focus and therefore ensures goal-oriented work. For example, in June 2017 we set up and launched Zalando Research as a place where we can focus and conduct cutting-edge research, and contribute actively to the research community in the areas of machine learning (ML), artificial intelligence (AI), natural language processing (NLP) and deep learning. Also, we have started to better organize teams to make sure we have a good ratio between research and engineering in the delivery teams. It became clear relatively quickly that clarity on the different research related job roles is very important as a foundation to organize research at scale. 

Reiner Kraft
Reiner Kraft, Zalando VP Search & Personalization.

We have created three different job roles and profiles that outline how we organize research within Zalando. All three roles have one thing in common; each person within these roles is a researcher. What makes them different is their focus and interest. We have:

  • Research Engineers
  • Data Scientists
  • Research Scientists

As we have iterated and refined these roles I wanted to share briefly how we distinguish them, and why it is important to think about these positions as part of your career growth, if you’re working in one of those areas. 

First, the research scientist is a very senior and experienced researcher, has a PhD in Computer Science or related discipline, a minimum of 3-5 years of relevant research experience (both academic or industry-based) in the area of ML, and a strong publication track record. Research scientists are not engineers, and they work in Zalando Research to produce world class research, to help shape our products, publish and present papers at top conferences, file patents, and otherwise help to promote Zalando Research as one of the premier research labs in the world. A research scientist usually focuses on continuous learning/experimentation as part of their research activity and is usually less interested in administrative, engineering or management type of work. We also offer a place for research scientist postdocs who have recently completed an excellent PhD to provide an environment that helps them grow their research experience. 

Research Lab

A data scientist is also a researcher, but in their education focused primarily on the topics of data science, and therefore has a very strong background on data science. The area of data science typically comprises topics like statistics, applied math, operational research, data mining/modelling, and related disciplines. Data scientists work in the context of a delivery team, and can do basic engineering tasks to help them get their experiments done, but are not aspiring to be engineering experts. If a data scientist fulfills the requirements of a research scientist, a data scientist could also work in Zalando Research (and then would become a research scientist). Similar to research scientists, data scientists are encouraged to publish papers, file patents, and actively contribute to the research community, as long as it is in line with the delivery goals of their team.

Last but not least, the research engineer combines strong research skills with comprehensive engineering experience. Similar to the “full-stack” engineer who combines front-end and back-end expertise, a research engineer combines research and engineering, and therefore is able to work relatively independently on researching complex ideas and pushing them on their own into production by writing production quality code.

Usually research engineers work in different “modes.” They start out with an idea, explore and evaluate it (“research mode”) for some weeks, and then once they have proven the merit of the idea they go into “engineering mode” to implement their idea into a production system (also for some weeks). After that, they go back into research mode and so on. Often research engineers get stuck maintaining a system they developed, which prevents them coming up with more original research. Therefore it is recommended to strive for an ongoing balance between research and engineering. Similar to research and data scientists, research engineers are encouraged to publish papers, file patents, and actively contribute to the research community, as long as it is in line with the delivery goals of their team. 

Zalando SE Innovation Research
Zalando Research, launched in 2016, brings together internal experts and scientists.

So why is it good to know what research role you are you currently fulfilling within Zalando? It’s simple: this is about career development and your “tour of mastery.” As a prerequisite, one first needs to know what role they currently fulfill. A good first step would be an initial discussion with your practice lead (PL) around this topic. Your PL is familiar with these roles and can help you assess better what role you are currently fulfilling, and can provide answers to your questions. Also your delivery lead (DL) can provide good insights, in terms of expectations around meeting the delivery goals of the team.

As part of a tour of mastery discussion there are a variety of options to advance in your career. Some examples:

As a research scientist you may feel the urge to get closer to product and delivery, therefore migrating more into a role of a data scientist or research engineer. In the latter, ramping up on engineering skills is important. Or, continue on broadening and deepening your research expertise to grow your career. 

As a data scientist you may feel the urge to ramp up your engineering skills to become a research engineer. Or, you may like to focus more on core research, not within the context of a delivery team or product to eventually become a research scientist. In this case you would need to work on your publication track record or on fulfilling all requirements that are needed to become a research scientist. Alternatively, you can continue on broadening and deepening your data science expertise to grow your career.

As a research engineer, you may be interested in broadening/deepening either your research and/or engineering skills, or you may prefer to work more in a research environment as a research scientist. In this case, you would need to work on your publication track record or on fulfilling all requirements that are needed to become a research scientist. 

I hope this article helps to clarify the differences between the research related job roles, helps you better understand what role are you fulfilling currently, and also gives you some ideas on your tour of mastery and career growth. 

Got questions for Reiner? You can find him on LinkedIn.

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