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Radovan Picek

@radovanpicek

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I build predictive models and actionable insights from complex data using Python, R, and statistics.

Czechia

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What I'm looking for

I'm looking for analytical work where I can apply predictive modelling, Bayesian statistics, and data analysis to practical problems, collaborate with others, learn new methods, and deliver measurable impact through clear, actionable insights.

I've worked on analytical models, statistical simulations, predictive modelling, and data analysis across the energy sector and academic research.

At SOLAR GLOBAL a.s., I worked as a Data Analyst, applying data-driven analysis in the energy sector. My projects have included battery storage optimization, missing-data methods with the Czech Statistical Office, and biostatistical analyses within a multidisciplinary research team.

I'm completing a Master's degree in Probability, Mathematical Statistics and Econometrics at Charles University's Faculty of Mathematics and Physics. I enjoy turning complex data into clear, actionable insights and am particularly interested in predictive modelling, Bayesian statistics, and practical analytical work with measurable impact.

Experience

Work history, roles, and key accomplishments

Current

Banking Specialist

Current

ČSOB

Oct 2025 - Present (10 months)

Works as a Banking Specialist at ČSOB, applying analytical and statistical skills in a banking environment.

Data Analyst

SOLAR GLOBAL a.s.

Dec 2024 - Sep 2025 (9 months)

Worked as Data Analyst at SOLAR GLOBAL a.s..

Econometrics Python Data Visualization Data Science R Data Analysis

Education

Degrees, certifications, and relevant coursework

Charles University

Magistr (Mgr.), Probability

2023 - 2026

Coursework included statistical modelling, machine learning, data science, econometrics, Bayesian statistics, time series analysis, stochastic processes, generalized linear models, optimization, mathematical finance, and programming in R and Python.

Charles University

Bakalář (Bc.), General Mathematics with specialization in Stochastics

2019 - 2023

The program provided a strong foundation in mathematical analysis, linear and abstract algebra, measure theory, probability theory, and mathematical statistics. It also included programming in R and Python.