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Konstantinos Stavropoulos
Senior Data Scientist (OTTO BI)
About me
I have been working since March 2022 at OTTO as Senior Data Scientist in Team IncAI. Previously active as Research Scientist as a mathematician and then as NLP Machine Learning Engineer, my current interests at OTTO range between classical data science topics -such as time series forecasting- and deep learning approaches, in particular in Natural Language Processing. Balancing everyday work-routine and sharing my passion for new technologies with other colleagues and teams in OTTO-BI is a value that I actively strive for.
My articles
Christian, Jürgen, Konstantinos, Tobias, TungNovember 15, 2023Dagster: Data Engineering Best Practice during Slack Time
In the inc(AI) team, we are always trying out different tools and methods. Slack time has proven to be a good way of doing this, in which we learn alone or together. The motivation for such Slack time naturally comes from the challenges that we have to solve during our work. Our strategy is to always look to the open source community first to find suitable solutions for us. Some time ago, we also investigated a new tool called Dagster in our Slack time.DevelopmentWorking methods- Christian, Jürgen, Konstantinos, TobiasAugust 17, 2023
ProductGPT – automating the creation of product texts with ChatGPT
Although they've been around for a while, Large Language Models (LLMs) have taken the world by storm since ChatGPT was launched. ChatGPT currently dominates the AI landscape like no other model. Could it also be used for the creation of good product texts in the OTTO Webshop? This is precisely the question we wanted to tackle in the inc(AI) team in a 2-week sprint. The result is ProductGPT – a tool that can do exactly that!DevelopmentMachine learning 
Christian, KonstantinosApril 04, 2023Return-rate forecasting with survival analysis
Especially in OTTO's retail business, accurately forecasting return rates and their fluctuations plays a major role in minimising unnecessary costs. In large-goods deliveries (fridges, sofas etc.) every single return results in very significant costs.Data scienceWorking methods- ChristianDecember 16, 2020
#3 Bid optimisation
In our last post we looked at how we use a sequential algorithm to achieve optimal user-campaign assignment. But this only gets us halfway to good campaign performance; the key is the bidding strategy.Development - ChristianDecember 09, 2020
#2 KPI Forecasts & Assignment
We want to address the following problem: an advertising partner wants to show its campaigns to the most suitable users possible, for instance to optimize click rates or increase reach.Since we have a large number of campaigns and advertising partners but can naturally fill an advertising space for a user just once. In the article, we'll provide solutions.Development - ChristianDecember 02, 2020
OTTO Display Network & COMPASS
For some time now, OTTO has relied on an in-house developed programmatic stack, the OTTO Display Network (ODiN). Through the correct application of data science, the implementation of campaign selection and the bidding service can be automated to a high degree. The following blog post is intended to provide a small insight into this implementation – the product we call COMPASS.Development
