Резюме Junior Business Analyst

Исходный текст

EDUCATION

School:

• International lyceum “Grand”, 2011 – 2017 (graduated with a gold medal)

Bachelor’s degree:

• Faculty of Computer Science & Cybernetics, Taras Shevchenko National University of Kyiv, 2017 – 2021.

Master’s degrees:

• Faculty of Computer Science & Cybernetics, Taras Shevchenko National University of Kyiv, 2021 – 2023

• Faculty of Economics, Corporate finance, Taras Shevchenko National University of Kyiv, 2021 – 2023 (with honours)

KNOWLEDGE & SKILLS

Calculus:

• Integrals, double\triple integrals, derivatives, partial derivatives, Taylor series, Limits, etc.

Differential equations:

• Solving different kinds of differential equations of first or higher order, solving systems of differential equations.

Game theory:

• Basic concepts of game theory, Methods of game theory, Zero-sum game theory, Games of imperfect information, Pursuit-evasion differential games, etc.

System analysis:

• Basic concepts of system analysis, SDLC, familiar with different types of diagrams.

• Completed course on Coursera.

Probability theory & Mathematical statistics:

• Basic derivations, common distributions & their derivations, finding mean, variance etc. of a given distribution. Basic knowledge of statistics for data analysis.

Basic knowledge of concepts and methods of Object-Oriented programming:

• Used OOP throughout studies in various different languages. Familiar with Encapsulation, Abstraction, Inheritance and Polymorphism and applied these principles in coding.

Data analysis and data science:

• General knowledge of data analysis cycle: data extraction, data cleaning, filtering, sorting, scaling, data analysis and data visualization.

• Analyzed different datasets during master’s degree study and edX courses. Basic knowledge of statistic for data analysis. Used different python and MC Excel tools to analyze cryptocurrency data, stock market data, Airbnb prices, NLP data, house sales, car prices, etc.

• Participated in different data science team projects as well as trained my own models as part of computer science master’s degree study. Trained NER models to analyze news websites for specific linguistic entities, trained Airbnb prices models to predict prices on certain properties in future, etc. Studied and compared different classification approaches as part of machine learning courses, tested them on provided data.

• Completed many edX courses on data analysis with excel and python

Economics:

• Basic knowledge of micro- and macroeconomics, financial markets and instrument, financial reporting and analysis.

• Familiar with balance sheets, income statements, cash flow statements, statements of shareholders’ equity.

• Familiar with technical analysis, common figures and trends. Analyzed different currency pairs data on MQL5 (Meta Trader 5). Familiar with moving average and standard deviation approaches to analyze trends, as well as different oscillators (FI, OsMA, RSI).

• Familiar with investment portfolio evaluation as a part of Investment Portfolio Management course of corporate finance major.

Research skills:

• Experience with theoretical research, did a coursework paper on use of fuzzy sets to analyze country’s default probability.

• Experience with theoretical research and conducting practical experiments in bachelor’s thesis on “Analysis of default risk based on fuzzy sets”

• Experience with theoretical research and conducting practical experiments in master’s thesis on “Solving traveling salesmen problem with subjective evaluation of travel time” (computer science major)

• Experience with theoretical research and conducting practical experiments in master’s thesis on “Analysis of bankruptcy probability of the corporation” (corporate finance major)

EXPERIENCE WITH PROGRAMMING LANGUAGES

Python skills: general, matplotlib, NumPy, plotly, pandas, MITIE, sklearn

• Used python in majority of assignments during bachelor’s degree. Implemented dynamic\static linear systems, used matplotlib for visualizing the dynamic of the system in a particular time period, used NumPy for its toolkit to easily work with vectors and matrices. Used NumPy for access to different statistical functions

• Used plotly to visualize data related to bitcoin prices in particular time period.

• Used matplotlib for data visualizations in different data analysis assignments, including fuzzy controllers, different types of plots and diagrams, graphs visualization, etc.

• Used pandas in majority of assignments in master’s degree study and several data analysis projects, including master degree thesis. Basic knowledge of data extraction, data preprocessing and data analysis with pandas.

• Used MITIE for training NER models for master’s degree thesis.

• Used sklearn to train/test different models related to Airbnb prices, stock market, etc.

Basic knowledge of C++

• Learned C++ for first year of university and used it for assignments concerning Data structures, Basic algorithms, Multithreading and concurrency, etc. throughout several years of study.

Basic knowledge of SQL

• Learned SQL in 2nd semester of 4th year of bachelor’s degree studies as a part of Database course. Made multiple SQL requests as assignments in MS Access.

Basic knowledge of HTML and CSS

• Learned HTML as a hobby during graduating year at school, made multiple HTML websites, attended couple HTML contests.

OTHER TOOLS & SOFTWARE

Familiarity with Matlab

• Learned Matlab in 2nd semester of 2nd year as part of Foundations of Database Design course.

• Used Matlab for assignments: Building basic Fuzzy inference systems, building basic Sugeno fuzzy inference systems, Simulating using a fuzzy system to control a construction crane \ air conditioning, fuzzy clustering, building a basic adaptive neuro-fuzzy inference system (ANFIS)

• Used Matlab for bachelor’s thesis to easily work with fuzzy sets and visualize them.

IBM Cognos Analytics

• Used Cognos Analytics for creating advanced dashboards with useful charts to analyze given dataset.

APIs

• Used CoinGeckoAPI to retrieve bitcoin prices data for certain period of time.

• Used IBM Watson Speech to Text API to transcribe audio files to text.

• Used IBM Watson Language Translator API to translate text from English to French and other languages.

Familiarity with Maple

• Used maple to simulate predator \ prey population behaviors as assignment in year 4 of bachelor’s degree.

• Used excel and maple for assignment on economy: Input-Output Leontief models, Single-Product manufacturing models, Impact of Government regulation on Supply\Demand.

Knowledge of Excel

• Data Cleaning

• Filtering and sorting data

• Data Analysis

• Data visualization with advanced charts and pivot tables

Knowledge of PowerPoint, Word, Access, etc.

• Used majority of MS apps during my entire bachelor’s and master’s degree studies.

Knowledge of Adobe Photoshop, Gimp, Final Cut Pro, familiarity with Adobe Illustrator, Premiere Pro, After Effects, FL Studio, TikTok

• Learned many editing apps for different projects in social media.

OTHER SKILLS & ACCOMPLISHMENTS

Courses passed

• Analysis for Business Systems (Coursera)

• Data Analytics Basics (edX)

• Analyzing Data with Excel (edX)

• Data Visualization and Building Dashboards with Excel and Cognos (edX)

• Python Basics for Data Science (edX)

• Analyzing Data with Python (edX)

English language

• IELTS overall band *********/9.0, equivalent to CEFR English level of C1.

Scholarship

• Received Government scholarship for high performance in studies during *********th semester of bachelor’s degree studies and 2nd, *********th semester of master’s degree studies

SOFT SKILLS