My First Month at Trendyol
I have recently joined the Data Science Team at Trendyol, which works to develop forecasting models through statistical models and machine learning algorithms with a goal to deliver a better experience to Trendyol customers. The team is made up of 12 domains covering Homepage, Recommendation, and Search, and I became a part of Customer Experience out of these 12 domains. In this article I will focus on my first impressions of the team for both those who are curious about Trendyol in general and the Data Science team in particular.
The Recruitment Process
It all started when I joined the Datathon Trendyol had organized a couple of months back. In the competition that was run over the Kaggle platform and lasted two weeks, we were expected to forecast whether the products would be returned or not. I truly enjoyed working on the rich dataset including order, product, customer, and seller details. Afterwards, Trendyol gave me the opportunity for a meeting, and following a rapid recruitment process I received an offer.
After I was recruited, I knocked on the door of every friend who has ever worked at Trendyol. They all mentioned the plusses of the Trendyol culture, details to follow below, and its significantly likely to happen contributions to my personal and technical development, and played a huge role in my decision to get on board.
Onboarding
The fact that Trendyol sent my whole package one month ahead of my start date showcased the unique professionalism of the onboarding process and the trust they have in their employees. A week prior to my start, a team member assigned as my buddy called to check in and meet. These are seemingly minor yet major details in this day and age he when we start working remotely from the get go.
Finally, my first day rolled around and my Trendyol adventure started off to a warm welcome by the team in the daily morning meeting. Next, my buddy and I went on to complete the onboarding steps we would follow for the next two weeks. A prepared Google Sheets under my name including all the steps, responsibilities, planning, crucial links, a reading list, slack channels, and much more important information was already in place. In addition, I was introduced to Trendyol’s much valued feedback culture via the “Feedback” page where I could share my suggestions for improvements to the onboarding process, which had already, went above and beyond my expectations.
After a quick setup in the first two days, I started to discover Trendyol’s tables. The puzzle started to take shape in my head as my teammates shared the details on the projects under the Customer Experience domain, which I am a part of. In the mean time, all the other domains brought the other new members and I up to speed in the onboarding sessions where they went over their projects and put us in the overarching Data Science team picture.
Trendyol Culture
I got to understand the meaning of the heavily emphasized “Trendyol Way of Working” through a packed 3-day Trendyol general onboarding program I attended along with the Data Science specific onboarding programs. In a nutshell, Trendyol harbors a happy work environment of ownership, free of egos and titles, where data speaks and practical Excel overrides elaborate PowerPoint, where active communication, feedback, insights and productive time management reigns over long winded meetings, where sharing and collaboration are encouraged and effort is appreciated and recognized.
Project Handover
The second week flew by with taking over a leaving mate’s projects. It is not like I wasn’t scared of shouldering so many projects at once but my teammates didn’t let me feel the load at all. Keeping all the docs on Google Sheets and the codes on Gitlab available to everyone enabled me to adapt to projects rapidly; I could find whatever I needed right away.
Rotation is encouraged at Trendyol both in terms of moving projects forward and its contribution to personal development. In line with that, a teammate started to hand over the projects to the rest of the team as she was rotating to another domain within Data Science. I assumed a few more projects that way. Project handovers were tiring yet enjoyable for me since, despite many companies, as the Data Science team at Trendyol, we can spend more time on modeling and spend almost none on ad hoc analysis.
Being a Part of the Trendyol Data Science Team
At Trendyol, we strive to make small yet continuous improvements via iterations instead of trying to reach the end results right away. We run an A/B test on each iteration before we green light it. We try to raise the quality of our code and our productivity by working on tasks in pairs as much as possible. When it is time for a new iteration to go live, we run a code review as a team to put everyone in the picture and to enable activation with fewer errors.
The biggest advantage to working with a team that’s knowledgeable in every aspect of Data Science is to be cultivated by the team with new information all the time. We encourage this by sharing our insights with the team through the weekly “Think Tank” sessions before we under take any major preparations. Furthermore, we discuss topics we want feedback on regularly in the internal brainstorming sessions twice a week.
In a short while, I had the opportunity to activate the new versions of two projects. The enabler behind that is the existence of a culture that allows for ample room to maneuver for the team and galvanizes productivity by equipping them with top notch applications, therefore, empowering the team to trail blaze towards a goal in common coupled with the active contribution of the team by continuous drive to learn and improve.
