Data makes the difference, algorithms are for everybody. While I more than enjoy data modeling, I am fully convinced that competitive business advantage comes only with the right data strategy. My mission is to embed this mindset into company cultures and businesses.
Creating innovative, data-driven, scalable e-commerce solutions together with a small team.
Particularly related to supply chain transparency and large-scale market analysis.
My focus lies on the successful set up of myconics' IT and Analytics infrastructure. Nevertheless, being one of two founders, I am equally involved in topics surrounding strategy, funding, branding and marketing.
myconics (“my iconic pieces”) is an online shopping platform for sustainably produced lifestyle products. www.myconics.de
Part-time engagement while still working full time at Daimler AG.
Working towards the AI-powered transformation of controlling and reporting in the Daimler Trucks unit. Besides heavy process automation, we focus on estimating the future development of relevant KPIs, collaborating closely with the respective business departments in an international environment. Tasks and tools include:
Tasks and projects (excerpt):
Title: "Dealing with Missing Values in Time Series"
Writing my master thesis about dealing with missing values in time series data with a focus on multivariate sensor data that was collected at irregularly spaced time intervals. Besides the massive amount of data, a major challenge is finding appropriate ways of imputing missing data gaps in the series.
Specialization track: Data & Web Science with a focus on Data Mining, Machine Learning, Information Retrieval/Extraction and Business Intelligence.
Master Thesis: "Dealing with Missing Values in Time Series" in cooperation with the Robert Bosch GmbH.
Specialization track: Economics (focus on statistics, econometrics, macroeconomics).
The bachelor thesis reviewed methods and applications of data compression techniques, such as used in the ZIP file format.
Currently investigating state of the art forecasting models like recurrent neural networks (more precisely, LSTMs). Figuring out how to design ensembles of such models in order to harness the "wisdom of the crowds". The objective is to design an ensemble framework that is robust to the underlying data generation process. Major challenges are:
Please drop a mail to mail*at*saschakrstanovic.com for any inquiries.