lang-uk/recruitment-dataset-candidate-profiles-english huggingface dataset:
Position: Junior Data Scientist
Category: Data Science
Experience: 0.5 years | English: intermediate

Bachelor's degree in mathematics. 
Courses “Python for Data Science and AI”, “Machine Learning with Python”, “What is Data Science?” Coursera
Data Science Fundamentals by DataRoot Labs (in process)
Stepic "Программирование на Python" Bioinformatics Institute
Participated in the competition for data science students competition "Housing Prices Competition for Kaggle Learn Users".
Creative feature engineering.
Advanced regression techniques like random forest and gradient boosting.
I'm looking forward to working in team of specialists, which will give an opportunity to effectively develop my professional skills.
Position: Junior Data Scientist
Category: Data Science
Experience: 0.5 years | English: intermediate

3-rd place at IASA Data Science Champ
Pet Projects:
1. C++ neural network library. Absolutely from scratch with matrix operations parallelization.
2. Satellite Images Segmentation. Applied semi-, self-, and supervised techniques to the forest segmentation task.
3. Mushroom classification app. Used self-supervised learning + finetuning.
4. Inpainting project. Based solely on linear algebra.
5. L4Logic. Python GUI program to design and test circuits of logic elements.

Work Experience:
1. Eleks. Completed an internship in Data Science Office.
2. AB Office. Developed C# library to sign electronic cheques used in PRRO. Still in support.

Seek for:
1. Possibilities to help people employing my knowledge.
2. Further improvement of my skills in data science or computer vision area.
Position: Junior Data Scientist
Category: Data Science
Experience: 0.5 years | English: upper

Has passed such online courses:
- Basics of programming CS50 
- Machine Learning by Stanford University 
- Open Data Science
- Kaggle
Pet project - Telegram Bot that classifies news into positive and negative. 
It consists of 3 components:
1. Parser – gains news from BBC site.
2. Model – prepares text data, creates features using TfidfVectorizer, fits Logistic
Regression and gives predictions for the new articles. Solves the problem of sentimental
text analysis.
3. Bot – sends results of predictions to users as articles links
I want to develop as a data scientist, to use machine learning algorithms in my work.
I want to work in a team where there will be an opportunity to develop professionally, learn new methods and apply them in practice. I would like to work with a good product that benefits people.
Position: Junior Data Scientist
Category: Data Science
Experience: 1 years | English: fluent

Got a master's in Data Science from a top 10 university in the UK.

Modules included: Data Mining, Statistical Foundations, Python and R Programming, Forecasting and Predictive Analytics, Intelligent Data Visualisation, Optimisation and Heuristics, Statistical Learning, and Data Science Fundamentals.
Planning and Analytics internship at Lancaster University:
 •	Implementing predictive analytics techniques to model University and sector performance rankings to predict next year’s performance of Lancaster University.
•	Working in R, Tableau, and Alteryx, presenting data analysis results to technical and non-technical stakeholders.
Position: Junior Data Scientist
Category: Data Science
Experience: 0.5 years | English: upper

Coursera licences:
+ Data Visualization with Python
+ Data Science Methodology
+ Databases and SQL for Data Science
- Preprocessing and engineering data for analytics and visualization
- Model selection and evaluation with further feedback
- Configuring Jupyter Labs for connection over ssh in purpose to ability to work anywhere
- Multiple pet projects projects based on Data Science books and courses
- Couple major student projects such as OCR Telegram Bot, OpenCV Robot
- Tons of written JupyterNotebook for quality data analyze and model creation
- Continuous self-improvement during entire life ;)
I am eager and ready for fast enrollment in DS with further improvement in any DS field.
Position: Junior Data Scientist
Category: Data Science
Experience: 2.5 years | English: upper


Previous work experience

IBM Integration Developer
• Developed and supported IBM Message Broker services.
• Worked with cross-functional teams to analyze existing system implementations and designed new functionality solutions sat-
isfying business needs.
• Deployed the improvements on the test environment.
• Quickly found solutions to eliminate problems in a production environment.

It has always been my ambition to become a specialist in data analysis and find useful insights to improve the efficiency of the given products. 
While studying for my BSc in Computer Science at university, I developed a strong interest in using Machine Learning algorithms and Neural Networks to predict the behavior of various processes based on the available data. After working over 2 years as a IBM Integration Developer, I have a deep understanding of software development life cycle, CI/CD processes and Scrum methodology. However, this experience also highlighted my desire to use data for analysis and making meaningful predictions rather than merely maintaining infrastructure for its transfer.
Position: Junior Data Scientist
Category: Data Science
Experience: 0 years | English: intermediate


Projects: 
- Facial recognition: master diploma project on the research of the influence of face angle on recognition accuracy using classical methods of the OpenCV library and convolutional neural networks.
- Object detection and recognition: bachelor diploma project of leaf classification using CNN
Position: Junior Data Scientist
Category: Data Science
Experience: 1 years | English: upper

Original project:
My goal was to create model that can predict count of likes based on text and amount of followers. I have used Twitter API to take data about users and tweets( like the amount of followers, text of a tweet, count of likes, etc). Then I have preprocessed data with pandas and numpy. My next step was to create new csv with less data, because my laptop was not powerful enough. So, then I just preprocessed data (vectorized text and added to this vector count of followers). The last step was to make the model. I found the best model - it's Logistic Regression, which gives for me an 89% accuracy.
And I've taken part in the competitions on the Kaggle.
Python Developer / Data Scientist (October 2022 - August 2023).
Implement time series forecasting techniques for solar
prediction.
XGBoost(with trees) have been chosen as model for this
project, because first of all in this dataset we had almost no correlation between X and Y, so Linear Regression will not fit, resources was limited so LSTM was no use for this project. And among all tree models, XGBoost gives the best results. It gives best results due to many reasons, for example: regularization built in this model, it is ensemble method, it has good tuning due to parametrize.
Position: Junior Data Scientist
Category: Data Science
Experience: 1 years | English: fluent


Python knowledge

Experience in data annotation 

Experience in dataset creation 

Experience in creating simple ML projects 

Knowledge and understanding of ML algorithms 

Knowledge of machine learning concepts

Experience in image processing

Fluent English

Experience in Jira
Position: Junior Data Scientist
Category: Python
Experience: 0 years | English: fluent

GitHub: https://github.com/pxl-th - represents my current abilities
Python, Tensorflow, C++
Not interested in Web Development
Position: Junior Data Scientist
Category: Data Science
Experience: 0.5 years | English: intermediate


Python ( using libraries such as sklearn, keras, tf, pandas, numpy, scipy, matplotlib, seaborn), PHP, MySQL, Linux, JavaScript.

Experienced in NLP ( nltk, gensim, spaCy), practiced with CNN.

I have knowledge of regression analysis, statistics, testing of statistical hypotheses. 
I took a course in statistics, higher mathematics and probability theory at the university. Advanced training courses in data analysis on Coursera
Position: Junior Data Scientist
Category: Data Science
Experience: 0 years | English: upper

Laboratoire Réactions et Génie des Procédés (LRGP) - Research
Data Science Academy - Data Science bootcamp
QSS Anaytics - Capstone Pojects
Research about  Data Analysis of effects of the humidity for powder flowability in Nancy, France. Measures of the correlation of different types of sample powders in various conditions. ML projects on several data types such as, prediction about infection amount for further dates  "Coronavirus" and prediction model for home prices from given dataset .
Position: Junior Data Scientist
Category: Data Science
Experience: 0 years | English: fluent

Retail and FMCG sector professional with >10 years experience
ML based pricing, cross-sale, customer segmentation
Retail and FMCG sector professional with >10 years experience
ML based pricing, cross-sale, customer segmentation
Retail and FMCG sector professional with >10 years experience
ML based pricing, cross-sale, customer segmentation
Position: Junior Data Scientist
Category: Data Science
Experience: 0 years | English: upper

•	Create image classification model for predicting melanoma disease by picture of human mole;
•	Find and clear big amount of data from noise objects near of moles;
•	Construct CNN various models, measure their quality (accuracy, roc auc score, confusion matrix, F1 score, etc) and chose optimum one;
•	Modernize data by different methods of data decomposition, for instance: PCA, kernel PCA, NMF, etc.;
•	Grid optimization of various hyperparameters with cross-validation evaluation;
•	Get model with the most stable learning values of accuracy, val-accuracy, loss, val-loss, visualize them and plot polynomial approximation and residuals error area of learning lines.
Student of 4-th course experience executing data-driven solutions to increase efficiency, accuracy and utility of data processing. Experienced at creating data regression models, using predictive data modeling, analyzing different measurements of evaluating models and visualization of various statistical graphs.
Have studied mathematical statistics, mathematical analysis, probability theory, optimization methods, numerical methods, etc.
Position: Junior Data Scientist
Category: Data Science
Experience: 0 years | English: upper


Studied and wrote small projects and applications in C++ / Java / Python. 
Solved common problems of mathematical disciplines, particularly mathematical statistics and probability theory.
Studied the theory and applied problems of cluster/correlation /regression, and ANOVA analysis (SAS/Statistica).
Applied modern data analysis methods using Python (Pandas/NumPy/Scikit-learn).
Position: Junior Data Scientist
Category: Data Science
Experience: 0.5 years | English: intermediate


uData Tech (October 2018 - November 2018)
Junior Data Scientist
Projects Description:
1. Medicine project. Analyse the most frequent diseases from dataset by protocols and make association rules with related disease, symptoms and medical tests. Python was used for data analysis and model development.
2. Image classification to detection pneumonia. Transfer Learning (pretrained Convolutional Neural Networks from keras (ResNet50, VGG16) on the first layers and Dense layers in the end) was used to solve the project. 

uData School (May 2018 - September 2018)
Junior Data Scientist

Projects Description:
1. Medicine project. Based on the sequence prediction we got quality prediction model that helps doctors understand what disease risk has their patient. Recurrent Neural Networks (LSTM), recommendation systems, association rules were used to solve the project.
2. Finance project. Find out is the disposition effect good or bad.

Responsibilities:
• Preprocessing row data: cleaning, fill in the gaps, outlier detection.
• Visualization of data with Python(Matplotlib, Seaborn).
• Creation business features and building the model using machine learning and deep learning techniques.
• Obtained the working model for business.
Position: Junior Data Scientist
Category: Data Science
Experience: 0.5 years | English: intermediate


uData Tech
Position: trainee Data Scientist
Responsibilities: data preparation, research of betting market to find profitable niches, testing of well-known models in the market rates for the optimization of coefficients and winning in general, monitoring key financial metrics.

uData School
Position: student Data Scientist
Applied statistics and probability theory, the basics of machine learning for data analysis, work on the two projects: business and medicine.

Freelance
Position: Private math teacher
Responsibilities: teaching different approaches to problem solving for passing the main tests after graduation and entering the university, admission test to groups and individual clients.
Position: Junior Data Scientist
Category: Data Science
Experience: 1 years | English: fluent


Vodafone Ukraine, Kyiv, Ukraine - Junior Data Analyst
November 2021 – ongoing
Main activities and responsibilities:
 - preparation of reports and presentations on the implementation of plans
- preparation and description of statistical data and graphs
- working with SAS databases using SQL and Data Step
Main tools: SAS, MS Visual Studio, MS Excel, MS PowerBI

Centric IT Solutions Lithuania - Junior Data Scientist (Internship)
May 2022 - August 2022
Main project: Optical Character Recognition for processing of relocation forms for municipalities of the Netherlands:
Main activities and responsibilities:
- pre-processing investigation of capabilities and limitations of MS Form Recognizer
- model training using MS Form Recognizer
- creation and implementation of unit tests using pytest
- further bug fixing and optimization within OCR project
Main tools: Python, MS Form Recognizer
Position: Junior Data Scientist
Category: Data Science
Experience: 0.5 years | English: fluent


Work experience   

Outreach (Remotely)
Contract Data Annotator
(September 2022 - November 2022)
     • Manually curated data through the review of audio datasets from unstructured sources by labelling them to define topics and speaker's reaction
                                                                     
ZEPS.Tech (Kharkiv, Ukraine)
Machine Learning Engineer
(July 2021 – March 2022)
    • Took part in application for gesture control and drawing development (Pose estimation, Gesture recognition).
    • Took part in drone with autonomous flight using tags development (ArUco & Apriltag markers detection and pose estimation).
    • Developed models for Image Classification and Object Detection (Machine Learning, Transfer Learning, Object Detection, Image Classification).
Position: Junior data scientist / analyst
Category: Data Science
Experience: 1 years | English: fluent


Looking for a data analyst position.

Master degree in biology with a diploma work in bioinformatics.

I have internship experience in Transparency International of Ukraine as Data analyst.

Technical skills: Python and libraries for data analysis (numpy, scipy, matplotlib, pandas, scikit-learn and others).

Also, I have experience with R, BI tools (Subset, Tableau), regex, bash, REST & GraphQL APIs, Jupyter notebook, Git, Docker, Flask, PySpark, MySQL, basic machine learning algorithms.
What I'm looking for:
-- Professional growth, obtaining new skills, improving existing knowledge;
-- Interesting tasks;
-- Place with friendly environment.

Don't consider:
-- companies without clear recruitment procedure (IQ tests, etc.)
-- companies with unpaid test tasks for a few days/weeks.
Position: Junior Data Scientist / Computer Vision / ML engineer
Category: Data Science
Experience: 3 years | English: upper

Methematics and physics competition achievements during school.
Academic success at profile disciplines in university leading to Bachelor's degree.
Team appreciation at previous place of work due to quality code, quick expertice gain, good teamwork practices, proactivity and communication.
ERP Developer at Innoware for 4 years:
Gained expertice in coding complex data manipulations and did a lot of tough legacy code debugging. In addition gained solid сollaboration and coding skills there.

Bachelor's degree in Software Engineering & ongoing Masters education:
Got to work in lots of different areas including ML/DL and to code in languages including C++ and Python. Gained basic knowledge in multiple areas including data science related subjects a-la statistics and probability theory.
Right now totally switching to Data Science area as I consider it the most suitable for me and my potential. I'd love to become part of team to consistently learn, exchange experiences and work on different kinds of ML projects.
Position: Junior Data Scientist / Data Analyst
Category: Data Analyst
Experience: 1 years | English: upper

•	Udemy,  Tableau 2022 Advanced: Master Tableau in Data Science.
•	Data Analytics Engineering Training, EPAM (6 month Training);
•	Microsoft Certified: Power BI Data Analyst Associate.
•	SoftServe Data Analytics Marathon (Power BI). 
•	Google Data Analytics Course on Coursera..
•	Udemy, The Data Science Course 2021: Complete Data Science Bootcamp.
I have almost a year of experience in a product IT company as a Data Analyst and more than two years in a research project in the field of data analytics in IoT.

The field of Data Analytics has captured my interest since the writing of my bachelor’s thesis. From that time on, I have constantly been trying to improve my skills in this area. My expertise lies in Python programming, where I emphasize statistical analyses, data visualization, and machine learning. I adeptly transform complex datasets into clear and insightful reports and dashboards,  using tools like PowerBI and Tableau. My practical experience extends to working with databases on platforms such as PostgreSQL and MS SQL. Beyond my technical skills, I am an active contributor to the scientific community, authoring articles, attending international conferences, and having several publications on the applications of Neural Networks in Data Analytics.

•	Programming languages: Python (TensorFlow, Pandas, NumPy, Scikit-learn, matplotlib, Streamlit, etc.);
•	Tableau;
•	Power BI (Microsoft Certified);
•	Databases: PostgreSQL, MS SQL, BigQuery;
•	VCS: GitLab;
•	Platforms: Mac OS, Windows;
•	Cloud Platforms: GCP (pet-project).
I am looking forward to interesting and challenging tasks, opportunities for professional growth and a friendly result-oriented team.
Position: Junior Data Scientist/Data Analyst
Category: Data Science
Experience: 0.5 years | English: upper

I rely heavily on data for my activism and hope to see evidence as base for our urban policies someday. More details are on my github page.
I spent some of my university years doing olympiad math. In particular, I helped to organize and jury events such as Ukrainian team IMO qualifications and EGMO-2019.
I've been working in finance as a data analyst/backend python engineer for 6 months as of now. I participated in building an SQL database, automated business tasks with python and used machine learning on several occasions. I also did reporting to company management.
I am happy to work with data in almost any form, though machine learning related tasks are preferred. I am more of a coder and have no experience with tools like PowerBI, Tableau etc. I also don't have any experience with Big data.
Position: Junior Data Scientist/Data Analyst
Category: Python
Experience: 1 years | English: upper

Working with big data
Solving problems of varying complexity.
Big data visualization.
Creating sites from scratch.
I worked with datasets using Python (libraries: NumPy, pandas, scikit-learn, SciPy, Seaborn), SQL.
Performed visualization using Power BI, Tableau, Matplotlib.
HTML, CSS, Bootstrap - to create websites.
Position: Junior Data Scientist/Data Analyst
Category: Other
Experience: 1 years | English: upper

- successful cooperation with US clients which led to increase of a team and a total revenue for the company;
- prefer to solve existing problems than create a new ones;
Python: Pandas, NumPy, Matplotlib, Jupyter, Seaborn, scikit-learn
R
Machine Learning: regression, clustering, classification
Sisense BI tool
SQL
- Opportunity for professional growth
- Definitely would be a plus cooperation with experienced members.
Position: Junior Data Scientist/Data Analyst
Category: Data Science
Experience: 0 years | English: upper

The Complete SQL Bootcamp: Go from Zero to Hero by Jose Portilla (Udemy)
Software Engineering student at Lviv Polytechnic National University.

I had experience with data manipulation and analysis using libraries such as NumPy and Pandas, creating visualizations and charts using Matplotlib and Seaborn.

Worked with PowerBI for data visualization and reporting.
Data Science with Python
Position: Junior Data Scientist, Data Analyst, Data Engineer
Category: Python
Experience: 1 years | English: fluent

Best Thesis Award 2020 at the American University of Central Asia

My thesis topic: Servant Leadership and Turnover Intention in Central Asia: A Test of Implicit Leadership Theory.
Work Experience:
- Data Scientist at Central Asian Bureau for Analytical Reporting for 8 months. My tasks include:data scraping, data cleaning, exploratory data analysis and Natural Language Processing in Russian and English languages.
Technology and lanugages worked with: Python(numpy, pandas, matplotlib, beautiful soup, TensorFlow), NLP libraries( NLTK, spaCy, scikit-learn, Natasha, Dostoevsky) HTML,  Jupyter Notebooks, Google Colaboratory, Visual Studio Code. 

- Poject Manager at Arniro Web Development Studio for 1 year. My tasks include: setting project timelines,  monitoring the status of project deliverables, updating relevant stakeholders and team members on the project's progress and delegating tasks to project team members.
Technology and methods used: Agile Scrum methodology and Trello for workflow

Education/Courses:
- Bachelor's degree, Business Administration, Financial concentration from the American University of Central Asia
I covered the following courses on Codecademy platform:
- Data Scientist career path
- Build a Machine Learning Model with Python
- Analyze Data with Python

Please find more information about my work experience  and education on my LinkedIn page: Atobek Rahimshoev
Position: Junior Data Scientist, Data Analyst, Finance Analyst
Category: Data Science
Experience: 1 years | English: intermediate

I am the captain of the winning team of NBU University Challenge 2020.
Programming Languages: R , Python.

I have experience using:
> Data processing: tidyverse, pandas, numpy, scipy, geopandas;
> Visualization: ggplot2, matplotlib, seaborn, plotly;
> Modeling: caret, forecast, nnet, randomForest, statsmodels, sklearn;
> Depp Learning: PyTorch (Computer Vision, NLP);
> Databases: SQL;
> Big Data: Databricks (PySpark, ML);
> Report/Application: R Markdown, ShinyApp;
> Cloud: Microsoft Azure;
> Git;
> StackOverflow;
> TIBCO Statistica.

I am finishing my master's degree in economic cybernetics. 
Therefore, I have knowledge of: 
> calculus;
> linear algebra;
> discrete mathematics;
> probability theory and mathematical statistics;
> econometrics;
> time series analysis;
> financial mathematics;
> economic theory and finance.

Additionally, I took many DS & ML courses (over 20 courses, specializations, projects) on platforms such as Coursera and Datacamp.

I successfully completed Kyivstar Big Data School 5.0 and entered the top-5 best students.
New experience and new achievements.