Nowadays I am passionate about operating complex systems and solve practical problems. I like when I feel that my work has direct effect, possibly positive. That's why I moved from 17 years R&D work in academia and a multi-national telco provider company to contractor positions in IT system operation where criticality of tasks is higher but solutions are straightforward, and I also became contractor in a small startup hedge fund where I was paid by success fee of my research results, i.e., live out-of-sample performance of my portfolio signals. Due to my strong background in R&D of mobile telecommunication, where the applied toolset from one part is theory, knowing internet and telco standards, data analytics, statistics, from other part development of prototypes, simulations, test environments, I tackle relatively easily with complex problems related to cloud operation, system administration, network configuration, and also have relatively strong analytical skills.In 2020 I made a transition in my career to quantitative portfolio management, alpha research, because of my interest in data science, data analytics, machine learning which only made up 10% of my work in Nokia Bell Labs. In the hedge fund my main task was factor development and research and regression model building for predictive trading. In practice they provided datasets, frameworks, libraries, and I developed and released Python Jupyter notebooks with new factor sets, new ML models, modified signal transformations, optimized hyper parameters. I also developed a sector-neutral SPY hedged close to close portfolio signal. Besides signal performance, memory consumption and signal generation latency was always important (data caching, saving and deploying ML models). Due to my telco background I supported also system administration work and solved cloud engineering problems such as automatization of data synchronization between on-premise and clouds or running hundreds of Jupyter notebooks in the cloud, I made several developments for AWS cost optimizations.