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$30 USD / hour
Flag of UA
slavutych, ukraine
$30 USD / hour
It's currently 11:50 PM here
Joined December 4, 2016
18 Recommendations

Volodymyr S.


5.0 (114 reviews)
$30 USD / hour
Flag of UA
slavutych, ukraine
$30 USD / hour
Jobs Completed
On Budget
On Time
Repeat Hire Rate

Counselor on Data Science, Mathematics, Physics

Coherent professional with a problem-solving mentality accompanied by many years of researching and teaching experience in Ukrainian universities. With superior quality in data modeling and simulation, I am confident my work will exceed expectations. Specializing in: - Projects pertaining to Statistical/Data Analysis, Machine Learning, Mathematics, and Physics. - Consulting Businesses through Financial/Inventory/Customer Data Analysis and Forecast. Skills that pertain to this project are the following: - Excellent Communicator - Problem-solver - Attention to detail - Analytical Thinker Analysis Skills: - Multivariate Statistical Analysis - Regression Analysis - Factor Analysis & Sensitivity Analysis - Bayesian Analysis - Monte Carlo Analysis - Experimental Designs - Time Series Analysis - Forecasting - Statistical Quality Control - Spatial Data Analysis - Structural Equation Modeling. Program Proficiency: - R programming - Rapidminer - Matlab - Python - Microsoft Excel. I do not outsource my work; I am a one-man team. Mostly available from 9:00 to 19:00 GMT+2
Freelancer Statisticians Ukraine

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Portfolio Items

This application estimates the high-frequency trading (HFT) profitability by analyzing Bids and Asks frequencies and optimizing P&L.
The application reads preliminary stored Binance an hour ticks history file of the selected symbol (click Choose Symbol to get it) and Fee (click Set Fee). 
Available at:
High-Frequency Trading profitability
This Shiny Web application is  available at It  reads and summaries the history of sales, trains a predictive model, and makes a forecast for the chosen number of days. The source of the data is a net of shops and stores SQLite database. 

Package ‘prophet’ is used to build the model and forecast. This is a very successful procedure which is based on an additive (or multiplicative) model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus (optional) holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well.
Sales Forecast (Shops & Stores Net)
This Warehouse Dashboard application implements Market Basket Analysis to mine the relationship between different products. It uses 'arules' package for getting rules and  'flexdashboard' package for Shiny.

The app tries to read the file '' with 'data.csv' inside, if it exists in the working directory. Alternatevely, you may choose a local CSV-file that contains the columns: 'Date' (as yyyy-mm-dd), 'OrderID', 'ProductID', 'CustomerID', and 'Qty.Logged'.
Market Basket Analysis: Shiny App
Market Prices Forecast (Daily Stock Trading) application ( ) is in support of the stock trading simulation to be built. It uses ‘Quantmod’ R-package for getting price history and ‘Prophet’ package for prediction.
Select parametes in the menu above. The drop-down symbols is the list of 514 ETF securities. It may be changed by placing the new symbols column in ‘symbol.txt’ file in the working directory.

Use the Forecast tab to explore predictions for the chosen symbol.

Click the Financial Analysis tab to examine standard financial charts. To learn more about the project, click the About tab.

Application author: vladishat
Market Prices Forecast Shiny Web App
In this project a set of complex polynomial roots was found with the help of Newton's method. The close vicinity of different roots where plotted down by the correspondent colors which form Newton Fractals. The solution was programmed and calculated in Matlab.
Matlab: Newton Fractals
The aim of the project was to find a pair of stocks sharing the common trend in such a way that a linear combination of two series would be stationary, which is so-called co-integration. The underlying logic of Pairs Trading is to monitor movements of cointegrated stocks and to look for trading opportunities when the divergence presents. Under the mean-reversion assumption, the stock price would tend to move back to the long-term equilibrium. As a result, the spread between two co-integrated stock prices would eventually converge. Furthermore, given the stationarity of the spread between co-integrated stocks, it becomes possible to forecast such spread with time series models.
The pair trading strategy includes looping over the stock pairs, extract two stock prices and estimate parameters. Next, we check the stationarity of that by using a special function that returns the result of two types unit root test. Then we create the trading signal using the estimated spread. A very simple tr
Stock Market Pair Trading Strategy


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Showing 1 - 5 out of 50+ reviews
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$200.00 AUD
Great personality. Very efficient and knows his code inside out. Highly recommended.
Data Processing Statistics Machine Learning (ML) R Programming Language
+1 more
Flag of AU Dan A. @dustyfog
7 hours ago
$100.00 USD
Great as always! Would rehire again, if possible!
Data Processing Statistics Machine Learning (ML) R Programming Language
+1 more
Flag of RU Alexey K. @AndrexF
22 days ago
$150.00 USD
Such professional work. Highly recommended
Statistical Analysis
Flag of US Rishi V. @varmapen96
29 days ago
$80.00 USD
Really helpful and patient person.No no need think twice go with him
Data Processing Statistics Machine Learning (ML) R Programming Language
+1 more
Flag of IN Nadeem S. @drshaikhnadeem88
2 months ago
$100.00 USD
Really knowledgeable person did whatever I wanted around the financial modelling
Data Processing Statistics Machine Learning (ML) R Programming Language
+1 more
Flag of IN Nadeem S. @drshaikhnadeem88
2 months ago



National Technical University of Ukraine Kiev Polytechnic Institute
Sep 2014 - Aug 2018 (3 years, 11 months)
My responsibilities included educational and scientific work, lectures on Artificial Intelligence, Data Mining, Decision Theory, Theory of Algorithms, Mathematical Modelling, Web-technology, and Web-design.


Donetsk National University
Sep 1999 - Aug 2015 (15 years, 11 months)
Lectures and scientific researches on Biophysics, Electromagnetic fields effects, Germicidal effect of high pressure food processing.


Doctor of Science

National Academy of Sciences of Ukraine
Doctor thesis "Effects of the band structure of solids in the inelastic scattering of slow electrons"


Sliding Mode Control of a solar power plant at weather fluctuated irradiance

Matlab/Simulink model of Sliding Mode Control was built to optimize a solar panel performance at a fluctuating by weather irradiance. This dynamic model shows a high performance relative to the pre-calculated Maximum Power Point Tracker, which may significantly improve the outcome of a solar power plant. Keywords: INUDECO, solar power plant, Matlab, Simulink, Lyapunov function.

Mapping of X-ray contamination. A digital model

This is a digital search and mapping of X-ray sources by means of a stationary set of sensors placed around the contaminated object. The problem was solved by the genetic algorithm. It was shown that in some cases of four and more detectors the X-ray sources may be mapped if their number does not exceed much the number of detectors. Keywords: Gamma-ray imaging, contamination, mapping, genetic algorithm.

Hidden revolution of human priorities: An analysis of biographical data from Wikipedia

Journal of Informetrics 10(1):124-131 · January 2016
A study of Wikipedia biographical pages is presented. It is shown that the dates of some historical cataclysms may be reproduced from peculiarities of lifespan changes over time. Categories were merged in just two classes. Being quite constant during almost the entire history, its ratio shows a sharp jump at the end of the 20th century mainly due to growth of Sport and Art groups over all others. Available at:

Parsing Wikipedia XML dump

CodeProject, April 2016
Article presents pretty simple parser for "pages-articles" XML dump file, capable of extracting body texts of pages, titles of pages with categories a page belongs, and names of categories with their parent categories. Body texts are not cleaned from markup, in particular because it may contain important information. For each Wikipedia's article page, calculate number of references to it from other pages. Available at:

Hierarchy of categories and classifying Wikipedia articles using XML dump

CodeProject, July 2016
A hierarchical object is built from relationships between categories and their parents. It is used in a classifier, detecting if an article belongs to possibly far parent category. Available at:

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Top Skills

Statistics 118 R Programming Language 115 Statistical Analysis 107 Data Processing 98 Machine Learning (ML) 38

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