lang-uk/recruitment-dataset-candidate-profiles-english huggingface dataset:
Position: Data Scientist
Category: Python
Experience: 1 years | English: upper

2010 – May 2021: Institute of Physics of NAS of Belarus, researcher
Responsibility: 
•	Optical end electronic experimental research of semiconductor structures
•	epitaxial growth on nitride heterostructures
•	Molecular beam epitaxy setup service
•	Software development for experimental setups
•	Analysis of scientific literature and writing scientific articles
Achievements:
•	developing software module for temperature calculation for Raman microscope
•	top 10 of NAS of Belarus achievements in 2016
•	more than 10 scientific articles in pre-reviewed journals
•	first observation of stimulated emission in CIGSSe films
Implementing from scratch (in the vectorized way, using just python/numpy):
•	Softmax classifier, Multi-class SVM,
•	Multilayer perceptron, CNN, with ReLU activations, dropout, batch/layer/group normalization layers with forward and backward computation path;
•	RNN, LSTM nets with tanh and sigmoid activations with forward and backward computation path
•	some first-order gradient-based optimization algorithms like SGD (+momentum, Nesterov momentum), RMS-prop, Adam. 

  Taking derivatives for all mentioned above neural net layers to do backpropagation
	
  Applying these algorithms to image classification (train on CIFAR-10 dataset) and image captioning problems (COCO). 

Implementing with PyTorch:
•	CNN with module API and sequential API and training them on CIFAR-10 dataset; 
•	multi-head attention transformer architecture (with module API) and combing it with DENSENET feature extractor for image captioning;
•	generative-advertising networks (LS, DC GAN) and training them to generate hand-written style numbers images that match the MNIST dataset; 
•	self-supervised SimCLR-like net, train it on unlabeled CIFAR-10 and then finetune it on the small amount of labeled data;
•	style transfer model with pretrained squeeze-net as a feature extractor. 
•	image gradient-based generator of fooling images, saliency maps, and class visualization images to neural nets.
Position: Data Scientist
Category: Data Science
Experience: 3 years | English: intermediate


Implementing major system for automatic pricing management for 20k sku and 14k clients

Developed system for automatic market analysis

Successfuly restructured the sales department of 200 people within 3 weeks  

formation of a training system for automation of pricing refactoring of the pricing algorithm

constructing additional algorithms for the price solution based on the significant characteristics of clients, goods, regions, financial conditions; 

implementing system of price management by sales managers; 

designing the main economic indicator of the company implementation of new logic for planning purchases and sales; 

developing the concept of processing market information and automation it. Integration to one system (import-export-internal resale) different data about spare parts, tires, automobiles, special technical equipment. 

Integration of this system with price analysis system. сlustering of сlients and Introduced Systems of "Packages of Services" for Clients;
 
Monetization of the company's services, and their next connection with price analysis system; 

developing methodology of forecasting company’s economic indicators; 

developing methodology of estimating economic efficiency of deals, goods, brands, clients, territories;
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: upper


Implementing SOTA neural network solutions in the NLP field;
PDF document recognition 
Entry quality control of product using CV
Optimizing and deploying neural networks:
Preventive maintenance system development
Worked on: semantic similarity tasks, document categorization, NER.
Currently located in Warsaw
Position: Data Scientist
Category: Data Science
Experience: 3 years | English: upper


- Implement the self-attention networks in Python and evaluate the UCR archive containing 128 univariate time-series datasets.
- A quantitative analysis and comparison with state-of-the-art
approaches
- Implementation of Grey Wolf algorithm that imitates the behavior
of grey wolves in nature to hunt in a cooperative way.
- Twitter semantic analysis of covid-19 virus - Collecting data
from Twitter using Twitter API, Applying NLP pipeline, and creating
model for regression analysis spread of the covid-19 virus.
- RPG Ontology - Develop ontology using Protege for well known
RPG game Dungeon and Dragons.
Position: Data Scientist
Category: Data Science
Experience: 0 years | English: upper

Instances of issues I have explained in my tasks identified with data science incorporate traffic sign classification, where I constructed a model to accurately identify traffic signs from images, and an employee attrition predictor, where I analyzed various factors to predict the likelihood of employees leaving the company.
In August I finished artificial intelligence and computer vision course and this really interested me. Computer vision is a new technology field that can change our lives significantly. I've been really inspired by Tesla technologies and how a simple car can make your life a lot easier and I truly believe we can implement this into our everyday routine. That's why I want to become a CV/ML engineer(professional) so that I can help ordinary people with the problems they face constantly.
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: fluent


In my current and past employment I have used R & Python to build economic models. These included, not exhaustively, assembling, manipulating, and analyzing immense datasets, often retrieved in non-structured forms; usage of API for data retrieval, using NLP model for classification, and etc.
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: upper


In my daily work, l do different tasks in data science team. I work in a company that offers professional data science, machine learning courses and services. By the use of data our team gives insights and solutions to business problems. Besides cleaning and preprocessing data, mostly l do modelling and predictive analytic tasks. I debug models doing bias variance analysis. On occasion l build boosting or bagging models to get high accuracy. I also make use of deep learning models for time series analysis. Most of the time l use python , but sql, excel, tableau also are in my toolbag.
Position: Data Scientist
Category: Data Science
Experience: 0 years | English: intermediate


In my github account i have been doing different python tasks. As well, I made two small games - hangman game and word game on python. Also i have a basic knowledge on C and Java. Besides, i have an Upper-Intermediate level of English and about a few years ago, studied French. 
Unfortunately, I can't leave a link on the git, as it is not possible to do on djinni.
First of all, improve skills, learn and implement new technologies.
Since, I haven't had work experience in the IT field yet, I can't say what I don't want to do.
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: fluent

One of my previous projects named, "Parallelization of bandit algorithms to reduce computational cost of news article recommendation systems." was selected for poster presentation at yearly project exhibition at UNIST.
In my previous internship, I was working with one of the state-of-the-art CNN architectures called “HRNet” to estimate poses from 2D data. Our experiments led to a 0.01% increase in the accuracy of the model. Prior to that, I was working on recommending news articles to the users using bandit algorithms. Our task was to reduce computation to provide services to multiple users in a short amount of time. Final algorithms increased the recommendation speed almost twice than the previous algorithms.
Currently, I'm more interested to explore the application of AI in real life since my previous works were mostly related to academia. I want to see how the state of the arts models react in real life scenario.
Position: Data Scientist
Category: Data Science
Experience: 0.5 years | English: upper


In my professional experience, I have successfully completed several key projects:

Gender Determination by Name for Latin American Countries:

Tasks: Analyzed large datasets to identify names and their corresponding gender distribution, cleaned and prepared the data for further analysis, and developed an algorithm for gender determination.
Technologies: Python, pandas for data processing

Data Visualization:

Tasks: Transformed raw data into informative charts and diagrams for better perception, analyzed trends and patterns in the data, and presented results to the team and stakeholders.
Technologies: Python, Matplotlib for charting

Word Cloud Data Preparation:
Tasks: Processed and curated text data to highlight the most frequently mentioned terms, ensuring relevant words are captured and any noise or irrelevant terms are excluded.
Technologies: Python, pandas for data processing, and specific libraries or tools tailored for word cloud generation.
Position: Data Scientist
Category: Data Analyst
Experience: 9 years | English: intermediate


In my role within the team, I have been involved in multiple projects encompassing testing, optimization, and development. I was part of a team responsible for testing a web application. I created test cases, performed manual testing, and reported any issues or bugs found during the testing process. I used testing frameworks such as Selenium for automated testing and JIRA for issue tracking. In other project  I focused on improving the performance of a mobile application. I conducted performance analysis, identified bottlenecks, and implemented optimizations to enhance the app's speed and efficiency. Technologies used included profiling tools, such as Android Profiler, and code analysis tools like lint. Regarding my role in the team, I have taken on various responsibilities depending on the project's needs. These have included working as a tester, optimizing performance, and contributing to development efforts.
In terms of improvement, I aim to enhance my skills and knowledge in several areas. Specifically, I want to deepen my understanding of automated testing frameworks and methodologies to further streamline the testing process. Additionally, I seek to expand my expertise in performance analysis and optimization techniques to continuously improve the efficiency of software applications. Lastly, I aspire to stay up-to-date with the latest technologies and development practices to ensure that I can contribute effectively to future projects.
Position: Data Scientist
Category: Data Science
Experience: 0.5 years | English: fluent

Took part in a lot of school competitions ranging from maths and physics to English, lingustics and literature. Regularly got prize places at the city stage of the competition (barely missed the country stage by 1 or 2 points a few times :c )
Innoware - Computer System Analyst | 03/2021 - 11/2021:
Working on a complex ERP system (Microsoft Dynamics 365), modifying the system, based on the customer's requirements, creating test-scripts for the functional product.

While attending various courses I've made:
- Fully functional FLASK applications for database management (flask-sqlalchemy based DB) and for dataset preprocessing and ML model training (with OOP project structure), that are also ready to be dockerized in a container;
- Stock market prediction using time series analysis, with comparisons of multiple algorythms and parameters for optimal results;
- Made models for image recognition using TensorFlow.

Took part in the EBEC Challenge Case Study team competition:
created and optimized short- and long-term plans for complex system management (d1: city development funds distribution, d2: Ukrenergo power system optimization and futureproofing).
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: fluent


Inspector | State Migration Service of Azerbaijan Republic Oct 2012 – July 2021
 Conducted inspections and evaluations to ensure compliance with migration laws and regulations.
Controller | Azersu Oct 2011 – Apr 2012
 Monitored water usage and distribution within the Surakhany Water-Canal department.
Founder| Market July 2006 – Feb 2008
 Oversaw day-to-day operations of a market/store, including inventory management, sales, and customer service.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: fluent


Instituto Gulbenkian de Ciência - (04/2021 - 09/2021) Oeiras, Portugal
Scientific Researcher
FCT fellowship to work on a project: Mathematical modeling of multispecies colonization dynamics – linking theory with data. Developed codes of  model with differential equations in MATLAB, R, and Python. Used mathematical, statistical, probabilistic methods, and numerical  analysis. Found relevant data and linked these data with theory. Wrote continuous reports.

Flash Data Pro Sh.p.k - (06/2019 - 03/2021) Tirana, Albania
Data Analyst
Gathered, cleaned and organized data for further interpretation. Identified patterns and trends in data sets. Used machine learning and data mining techniques for forecasting football data with high accuracy in R programming. Deployed a code to conditionally recommend other menu items based on past order history to increase average order size, and which products should be placed next to each other in supermarkets and bakeries to increase the amount of the purchased products. Implemented various time series forecasting techniques to built a costumer segmentation model that improved their loyalty. Also used optimization methods for maximizing profits of different businesses. Maintained Web Scraping projects (written in Python and R).
Analyzed large datasets. Reported the results back to the relevant members of the business. Demonstrated computer proficiency in Excel while working with statistical analysis and regression modeling.
Position: Data Scientist
Category: Data Science
Experience: 0.5 years | English: fluent

Education:
Master degree in Electrical Engineering. Radioengineering Faculty National Technical University of Ukraine "Kyiv Polytechnic Institute"

Courses:
-Python for Data Science and Machine Learning Bootcamp
-Python разработка - с нуля до профессионала. Python 3
-The Complete Python 3 Course: Beginner to Advanced!
-Complete Git Guide: Understand and master Git and GitHub
Interested in grows in advanced analysis and ML, keen on mastering and implementing new technologies.
Position: Data Scientist
Category: Data Science
Experience: 3 years | English: upper


Intern Data Scientist / Academic Mentor 
QSS Analytics/ Data Science Academy, December 2019 – July 2020 
1) Statistics and basics of Data Science 
2) Advanced Data Science techniques and tools 
3) Academic mentor in “Linux OS / Git version control system" , "R Programming", "Python for Data Science" , “Big Data" 

Intern Data Scientist 
e-Gov Development Center, June 2020 – September 2020
1) Data Cleaning and Data Manipulation using “pandas”, “numpy”, Regular Expressions and user-defined functions
2) Data Visualization using “plotly”, “matplotlib”, “seaborn”, etc
3) Predictive Modeling using “scikit-learn”

Intern Data Scientist 
Unibank, May 2021 – August 2021
1) Data Cleaning and Data Manipulation using “PySpark” and “pandas”
2) Data Visualization using “matplotlib”, “seaborn”, etc
3) Predictive Modeling using “scikit-learn”, “TensorFlow”, “hmmlearn”
Intern Data Scientist 
Pasha Bank, June 2022 – September 2022
Data Science for Credit Risk Monitoring: 
1) Improving existing Credit Risk Engine
2) Modelling customers' behavior and finding out risky clients
3) Reporting current Risk Engine's performance
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: upper


Internship at SPD-Ukraine
Dec 2022 – Feb 2023 | Cherkasy, Ukraine
During the three-month internship in the role of "Junior Data Scientist," I gained valuable experience and knowledge in the field of data analysis. Throughout this period, I successfully worked with various tools and technologies, including:

Python and Libraries: My work involved using Python for data processing, analysis, and visualization. I utilized libraries such as Pandas for efficient data manipulation, Numpy for numerical computations, and Matplotlib for creating graphs and visualizing results.

Machine Learning: During the internship, I familiarized myself with the basics of machine learning and the use of the Scikit-learn library to build and fine-tune classification and prediction models. This allowed me to develop simple models to tackle data analysis tasks.
Self employed
Feb 2023 – present
I work for myself as a freelancer, utilizing various technologies to gain valuable experience and provide efficient solutions to my clients. My skill set encompasses a range of tools including:
Aiogram: I'm adept at leveraging the power of Aiogram, a Python framework that simplifies the process of creating Telegram bots. This allows me to develop interactive and responsive bots for various purposes, from customer service to automating tasks.
PyQt5: Another area of expertise lies in PyQt5, a library for creating desktop applications with a graphical user interface. This skill enables me to design and build user-friendly software that meets my clients' specific requirements.
Pandas, Numpy, Scikit-learn: I am well-versed in these data science libraries. Pandas helps me efficiently manipulate and analyze data, Numpy provides the foundation for numerical computations, and Scikit-learn empowers me to develop machine learning models for predictive and classification tasks.
By working with these technologies, I am not only gaining hands-on experience but also constantly expanding my knowledge base. This ensures that I can provide tailored and innovative solutions to my clients' diverse needs, whether it's developing cutting-edge AI-driven applications or creating intuitive desktop tools.
Position: Data Scientist
Category: Data Science
Experience: 0.5 years | English: upper

EDUCATION
Computer Mathematics
Taras Shevchenko National Unuversity of Kyiv
09/2019 - Present.
Internship
Student Researcher 
Topic and Applied Technologies: Machine Learning and Signal Processing applied to analysis of bioacoustics signals

Internship
Analyst in product IT
Kyiv, Ukraine

I'm interested in every part of Data Science, Computer Vision, Databases.
Position: Data Scientist
Category: Data Science
Experience: 2.5 years | English: upper

Implemented custom neural network library in golang for educational purposes. Also created scaffolding app setting up environment for deploy; it's capable of configuring required 3rd-party service integrations, S3 buckets & tokens, Helm charts, etc., without a human intrusion.
In the current company I'm a part of the Platform team - we maintain infrastructure logic, monitoring and security services. Personally I have developed from scratch i18n app, scaffolding service for convenient quick deploy and cluster traffic monitoring distributed app. For the previous company designed and implemented real estate analytics service along with the whole production ecosystem.
Interested in highload system development. Passionate about web scraping & geo data. Also possible growth in the direction of ML & data engineering.
Position: Data Scientist
Category: Data Analyst
Experience: 0 years | English: intermediate

I had gained the diploma of excellence Masters of Economics. The Univercity gave me the opportunities that bring economic insights, value and strategic thinking to data science and modeling.
In the univercity I was a member of non-formal Economic club, played and had price place in univercity game "Brain ring".
In the univercity I have gained skills in economic modeling and intuition, big data analysis, econometrics, analytic storytelling, and effective communication of economic research results.
Pre-diploma practice gave skills and knowledge of how the enterprise how to count and reduce costs, how to be effective in competitive environment.
In 2012-2014 I assisted private entrepreneur (family business) with entering data into the accounting program and filling out tax documents.
Position: Data Scientist
Category: Data Science
Experience: 10 years | English: fluent

Finished PhD research in Scientific Computing
Authored 7 papers and submitted 10 patent proposals
In total I have 10 years of experience working as a software developer, advanced analytics consultant, AI and mathematics researcher/engineer. I also led several projects and teams.
I have been working with projects of various sizes from different business domains. Participated in all stages of project development starting from conceptual design, researching and prototyping, developing, client demonstating and pitching.

My main analytical skills include machine and deep learning, knowledge graphs, mathematical modelling, data assimilation. I am 
experienced with nlp, computer vision, time series and physical problems. I have a strong background in probability theory, statistics, linear algebra, numerical analysis, optimisation, estimation and control.

My main programming skills include: Python, Matlab, C#/.NET, SQL, WPF, Java, JavaScript, AWS, Docker. Main data science  tools: Pandas, sklearn, cpacy, keras, pytorch, tensorflow, numpy, OpenCV.
I am interested in lead/management positions with a technical emphasis.  
I am looking for challenging problems that require deep expertise (both domain and technical) and creative thinking.
Potentially interesting areas include: data science, computer vision, advanced analytics and mathematics.
Position: Data Scientist
Category: Data Science
Experience: 0 years | English: intermediate


I participate in Kaggle competitions and solve tasks of classification, regression and natural language processing mainly using scikit-learn, pandas, NumPy and statistical concepts. I use Matplotlib and seaborn for data visualization and have basic experience with nltk.

I got inspiration and understanding of supervised and unsupervised ML technics from Coursera tasks (completed ML course by Andrew Ng) and refreshed university knowledge with Stepik "Fundamentals of statistics".

I studied software engineering in Kyiv Polytechnic Institute. Graduated in June, 2019 from faculty of applied mathematics. Got programming and math skills, in particular Python, probability theory, statistics, web, SQL, git.
I am looking for my first full-time job in data science/machine learning/AI field. In this position I want to use current knowledge for real world tasks in team environment and - boost knowledge in directions of classical ML and deep learning