Work experience

Co-founder and Chief Data Scientist, Koios, 2023—Present
At Koios, my role involves developing and applying state-of-the-art audio deep learning models for predicting personality. I’ve designed an on-going data collection protocol, developing the technology from scratch, and rigorously tested validity of the predictions to ensure the clinical precision of our algorithms. My leadership also extends to deploying and monitoring algorithms in production, ensuring they deliver the highest possible value to our users.

Research Data Scientist, QuantCo, 2021—Present
At QuantCo, my work focuses on researching and building models, combining causal inference with machine learning, and creating reliable prediction systems. My main work revolves around fraud detection but our products include algorithmic pricing, data-driven claims management, and high-dimensional forecasting solutions.

Associate, Institute of New Economic Thinking, University of Oxford, 2020—Present
Following my research visit in Fall 2019, I became an Associate of the Complexity Economics program, led by J Doyne Farmer. The group uses tools from complex systems science to generate new insights into a wide range of economic problems. With Penny Mealy and R. Maria Del Rio-Chanona, we are currently developing a project focusing on skill use and retraining in the wake of automation and digitalisation.

LSE Fellow in Computational Social Science, Department of Methodology, London School of Economics and Political Science, 2020—2021
As LSE Fellow, I am mainly involved in teaching advanced courses in master’s programmes (MSc in Social Research Methods and MSc in Applied Social Data Science). I lead seminars in Data for Data Scientists and Applied Regression Analysis. My methodological research is focused on discovering heterogeneity of treatment effects and power analysis in conjoint experiments and how causal inference fails under violation of no interference assumption in networked social contexts (see poster here).

Researcher, Centre for Sociological Research, KU Leuven, 2016-2020
As a member of a Flemish Research Council (FWO) funded project on “How are social divides produced in contemporary European labour markets?” under supervision of Valeria Pulignano, Wim van Oorschot, and Bart Meuleman, I developed new research methodologies for measuring labour market segmentation in Europe by use of latent class analysis. I programmed an agent-based model of recruitment under reputation systems at online labour market platforms and used large web-scraped data to investigate segmentation in online labour markets.

Data Scientist, IBM International Services Centre, 2015-2016
Being part of the Client Experience team, I led several experimental and observational studies with focus on monitoring and improving customer experience. As part of my team’s efforts, I helped develop an automated early warning system that used text analytics to predict emerging problems during the sales process. I designed a study to measure a causal effect of an innovative sales’ practice on final transaction satisfaction. For these efforts, I received IBM Manager’s Excellence Award (2016) for contributions in statistics and data science. On top of my analytical work, I successfully advocated for a change in metric used for measuring client satisfaction from year-to-date to a 12-month-rolling, which is still in use. During my time at IBM, I shared my knowledge by teaching R and statistics to the Client Experience for Sales team.

Education

Ph.D. in Social Sciences (Computational Social Science), KU Leuven, 2021
Dissertation: Computational approaches to labour market segmentation, supervised by Valeria Pulignano, Wim van Oorschot, and Bart Meuleman
- Finished all courses in M.Sc. Statistics at the Leuven Statistics Research Centre (L-STAT)

M.Sc in Social Policy Analysis, KU Leuven, 2015
Thesis: The effects of democratic institutionalization and satisfaction with democracy on subjective well-being in Europe: comparing random and fixed effects multilevel approaches, supervised by Jacques Hagenaars

M.A. in Governance and Global Affairs, Moscow State Institute for International Relations, 2014
Thesis: Domestic factors influencing foreign policy: case study of Ukraine 2008-2012, supervised by Andrey Sushentsov