lang-uk/recruitment-dataset-candidate-profiles-english huggingface dataset:
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: upper


-Created models for regression, classification, clustering. 
-Created Machine Learning models for text similarity and fuzzy matching in big data. 
-Worked with H2O and Google Cloud for image classification.
-Developed Statistical Learning and Time Series Analysis for product sales.
-Used pre-trained models and OpenCV to develop object detection and tracking system.
Prefer working on financial or marketing projects, analyze and explain data, apply models to get the most value from the data. Expect to work with senior data scientist to learn from and a friendly team. 
Flexible working hours.
Interested in scientific research and playing board games after work:)
Position: Data Scientist
Category: Data Science
Experience: 0 years | English: fluent

created my own ml project. It predicts house price in Lviv city. It has a percision of 80 percent. Precision can be boosteed by adding new columns of features
created my own ml project. It predicts house price in Lviv city. ALgorithm that suits the most is Random forest regressor. I collected all the data and done all the coding by myself. My aim is to become ai researcher/developer
Design of anything
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: fluent


Creating a dataset for credit risk modeling purposes using SAS and SQL. 

Collaborate with subject matter experts to obtain, prepare, process, validate and complete the data required for relevant operational tasks.

Maintain a strong relationship with Business Representatives.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: upper


Creating connectors for a unique data ecosystem based on APIs(Facebook API, Google BQ API, Firebase API, Mixpanel API, Podio API, MailChimp API), Python and Data Studio. 
 Python(Pandas, Numpy, Sklearn, Xgboost, Seaborn and so on.)
 DS models: decision tree, random forest, gradient boosting models, clusterization,
regression.
 Creating dashboards in Data Studio. 
 Excel for analytics.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: fluent


- Creating scope of NLP models (text classification, entity extraction, topic modeling, text autocompletion) and converting them to IOS format
- Creating inverted video & image search system, including object detection, face recognition, and image classification tasks. 
- Conducting churn analysis, revealing behavioral factors affecting user retention, conducting behavioral customer segmentation for SaaS products
Position: Data Scientist
Category: Data Science
Experience: 2.5 years | English: fluent

• Master in Economics
  The main concentrations -Behavioral and Moder Data Analyses

•Master Research Topic Competition
 Issued by Fintech& Suptech Development at NBG at National Bank of Georgia 

•International Scientific-Technical Conference
Issued by Shota Rustaveli National Science Foundation of Georgia
Credit risk squad:
 • Creating machine learning models for credit risk scorecards(approval rate improved by 7%);
 • Designing an exploratory data analysis(EDA) and visualizing the loans request process to optimize 
 communication frequency;
 • Creating a machine learning model to predict pre-approved loans;
 • Communicating project deliverables and goals with business teams;
 
Customer activation squad:
 • Improving customer activation rate based on onboarding process by classification(XGBoost 
 classifier) and clustering(K-means) models;
 • Analyzing and predicting customers' product consumption behavior and churn rate;
 • Creating machine learning models(Python, Scikit-learn) to improve cross-sell ratio;
 • Translating data insights and key results for business teams;

Gamification squad:
 • Catching fraud detection by analyzing customers spending behavior;
 • Creating distribution of gamification leaderboard;
 • Design RFM scoring and analyzing customers movement into different clusters by PowerBI;
 • Creating and deployment CLV models on AWS;

Product improvement squad:
 • Creating a real-time card transaction categorization engine;
• New challenges  
• Learning new technologies 
• Working with an international team 
• Solving big scale problems
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: upper

•Master of Arts, Economics;
•Master's Degree, Mathematical Economics and Econometrics 
•Have experience of working with R, STATA, MATLAB, Python (scipy, numpy, pandas, scikit-learn);
•ML algorithms knowledge;
•Coursera certificates (Neural Networks and Deep Learning, Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization, Structuring Machine Learning Projects, Convolutional Neural Networks, Applied Machine Learning in Python);
•Experience with SQL/NoSQL databases
CSFL Research;
Teaching Assistant statistics and econometrics (1 year);
Data Scientist (2 years) 
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Data Scientist position.
Position: Data Scientist
Category: Data Science
Experience: 5 years | English: upper

- NLP data processing qualifying potential customer intent/need probability
- Automatic system for stock and options analyzing timeseries data for more than 10000 stocks and options
- CTO (AVIDА) - Developed system for marketing to identify potential customer based on messages in social networks and channels. BERT NLP Neural Network model was used and trained on gathered data. As a result from application the right moment to make an offer to the potential customer was identified.
- Implementation of automatic robotic dispensing of medications and related medical service platform, interop API to microcontroller hardware. 
Image Recognition was used to Identify Barcode on a package with medications. 
Lead and manage team (10 developers)

- Lead Analyst (HighTechInvest) Data Science (Time series) - Headed in the Advanced Back-testing system development with ability to perform simulated trading both in options and underlying securities.
Developed adaptive methods for timeseries data analysis.
Provided advanced mathematical methods for pricing vanilla options and facilitating trading decisions.
Performed quantitative analysis of option prices and trading possibilities.
Supervised trading systems development.
Controlled the database of financial data with full history for US stocks and options.
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: upper

Data science 
NLP project for topic detection, hot topic detection. Frequency key words analysis using metric methods of machine learning. Two scientific publications in Q1 journals on information science.  

Skills in physics
Teaching courses in quantum mechanics, mathematical analysis, electricity and magnetism, theory of complex variables, molecular physics ets.

Management skills
Project management for the creation of web application (https:\\grants.nrfu.org.ua) for the registration, expert assessment and reporting for applications that are submitted to the National Research Foundation of Ukraine. My main duties - preparation of technical specifications for building business processes for an automated system, negotiations with developers, preparation of accompanying project documentation, customers support, data analysis.
Currently Associate professor at National Taras Shevchenko University of Kyiv, Physics Faculty

Main research interests:
Statistical analysis of scientific knowledge recorded in scientific publications. Developing real proximity measure between physics ontology concepts and documents. Adopting this measure for multi-networks of physical concepts and documents.
 
Recent publications on data science
1. Chumachenko A, et al. Dynamical entropic analysis of scientific concepts. Journal of Information Science. November 2020. 
2.Chumachenko, A. V., et al. (2020). Dynamics of topic formation and quantitative analysis of hot trends in physical science. Scientometrics.
Work in a team that ready to share their experience flexible for research and to accept something new. Work online or offline (70/30) in Kyiv office. Ability to participate in data science conferences, seminars, etc.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: upper

Developed GPT-3 based product about which an article was written. Developed NER model that predicts specific parts in text data with 98% rate.
Currently develop game where every NPC is a GPT-3 based model and auto-trading bot. Developed recommendation system for sales department, NN that predicts sales volume by seasonality, algorithm that finds best selling pairs of goods for one of the biggest retail chains in Ukraine. Developed NN that predicts type of product by description in custom database, and neural network that finds facial features for one startup. Developed DL models for NLP tasks, multilabel text classification and text generation. Rebuilt improved automatisation data streaming pipeline. Developed recommendation system for sales department of one of the biggest retail chains in Ukraine and neural network that predicts the product type by its description. Also developed model that extracts face features and classifies goods from customs database, that imported in and exported from Ukraine.

Have an experience in:
- Developing and training NER and text multilabel classification models
- Training text generation model
- Developing recommendation system for sales department of one of the biggest retail chains in Ukraine
- Making datasets for model training, evaluation and testing
- Developing and training face keypoint detection model
- Developing and optimisation ETL pipelines
- Data analysis: processing, visualisation and evaluating
- Computer vision: classification, semantic segmentation, object detection
- Deep Q-Learning
- Optimisation of neural networks
- Exploratory data analysis
- ML algorithms: regression, classification and clustering

Tools and Technologies:
Deep Learning: Fully Connected Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks
Deep Learning architectures: 
- Computer Vision: VGG, U-Net, ASPP,  R-CNN, SSD
- Neural Language Processing: LSTM, Attention, Transformer
Machine Learning: Logistic Regression, SVM, Naive Bayes, Random Forest, Decision Tree, XGBoost, kNN, K-means, DBSCAN, PCA, SVD, t-SNE
Languages: Python, SQL
Tools: NumPy, Pandas, scikit-learn, TensorFlow, Keras, Tensor-RT, nltk, spaCy, BeautifulSoup, Parallel processing, OpenCV, Kivy (a little bit).
Visualization tools: matplotlib, seaborn
I would like to develop DL models for any applications. I do not want to spend a lot of time labelling and analysing data.
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: upper


Currently, I am a 4th-year Computer Science student at Lviv Polytechnic National University, and my passion for this field has driven me to excel both academically and professionally.

During my studies, I had the privilege of participating in various contests and hackathons, which allowed me to challenge myself and put my skills to the test. I was on top-performing teams in events like the Lviv Polytechnic National University Game Hackathons and the Facebook EMEA Virtual Coding Challenge. Additionally, my contributions to the OxML school Kaggle competition showcased my capabilities in NLP(document ESG classification).

In my professional journey, I am currently a Data Scientist at Integrated Technology Laboratory LLC, where I have been actively involved in building advanced machine learning models. One of my achievements includes developing models to predict cryptocurrency prices based on technical indicators and various currencies. I also implemented forward-chaining cross-validation techniques to enhance model performance and gain valuable insights. Through this experience, I have solidified my foundation in data science and machine learning.

In addition to my academic and professional endeavours, I have pursued various personal projects that reflect my passion for creativity and problem-solving. I thoroughly enjoy the process of creating unique solutions from scratch.

For instance, I developed a tool that accurately counts coins and calculates nominal values in videos, showcasing my proficiency in computer vision and data processing. Another project I undertook was an engaging card game that included a lie detection algorithm to ensure fairness during gameplay.

Creating these projects was an enjoyable experience, which allowed me to strengthen my skills and broaden my knowledge in different areas of Computer Science.

Overall, my journey has been marked by a relentless pursuit of knowledge and a passion for leveraging technology to solve real-world challenges. I am eager to bring my skills, enthusiasm, and dedication to contribute to new projects and make a positive impact in the field of Computer Science.
Position: Data Scientist
Category: Data Science
Experience: 0.5 years | English: upper

I have created a couple of pet projects such as:
- Credit Card Fraud Detection ML model
- Diamond Prices Prediction ML model
which are available on my GitHub.
Currently, I am an Engineer-technologist, involved in the R&D of novel coatings for gas turbine engines. Have a strong background in Material Science. Have a great interest in AI and Applied Science. Now I am looking for new opportunities in Data Science.
As an engineer-technologist, I am responsible for 
•	Development and implementation into the production of new technologies for applying protective coatings on turbine engine parts.
•	Analysis of experimental data, creating reports.
•	Search for high-tech equipment suppliers, negotiate with suppliers, support for the purchase and commissioning of equipment (acceptance tests and so on).

Also now I am working as a scientific researcher at university. I am involved in analyzing and cleaning experimental data, writing scientific articles. Took an active part in the organization of NATO Workshop "Spintronics Radar Detectors"

As Data Science experience I worked as Data Science Trainee in Data Root Labs, where I get Data Science fundamentals.
I am looking for opportunities to work in Data Science, develop in this direction.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: upper

BS in Computer Science
A second-year MS student at UCU Data Science Program

Deep Learning with PyTorch - Facebook Scholarship for Nanodegree Program by Udacity

Introduction to Computer Vision - Udacity's course was conducted by Aaron Bobick - dean of the School of Engineering and Applied Science at Washington University in St. Louis.

Machine learning A-Z - Udemy's course
Participation in the DataRoot University

Introduction to machine learning with python a guide for data scientists - the book was written by Andreas C. Müller, Sarah Guido. All about ML and python tools like sklearn, pandas, NumPy, matplotlib
Currently, I am a second-year MS student at UCU Data Science Program. I am also working as a machine learning engineer.
Previously, I worked as a machine learning engineer at Global Logic. Thus, I got a wide range of experience working with such CV algorithms as face aligning, face detecting, face recognition, etc.
Furthermore, all of these algorithms were converted and integrated with IoT devices such as Google Dev Board, Raspberry Pi and Coral Edge TPU, Jetson Nano. 
I worked as an intern R&D engineer at SoftServe, at the student program - R&D Incubator.  Thanks to this program, I got hands-on experience in the field of machine learning and computer vision. At this position, I worked a lot with object detection, object tracking, and especially face detection, and also it was the central part of my previous project and my course work. One of the challenging task was model deploying. As for this goal, we use Movidius Compute Neural Stick.
Moreover, I like to prove my skills in different competitions and hackathons. For example, my team and I took first place in the Garage48 hackathon with project PropaGANda. In this start-up, we use Long-Short Term Memory Neural Network for sentiment analysis of Ukrainian text. The main idea was in detecting too emotional news because it is a good indicator of manipulating. Besides that, our team took 3rd place in Megogo Kaggle Challenge. In this competition, our task was to make a movie recommendation algorithm.
Furthermore, I fond of reading computer vision papers and use the current state of the art in my project. Also, I have one student paper that paper wrote based on the Facial expression recognition work. I usually use Numpy, pandas, OpenCV, and matplotlib for some preprocessing and visualization in my applications. PyTorch or Keras/Tensorflow for neural nets.
I fond of interesting projects, where I could use state of the art deep learning algorithms. I am open for new suggestions and will be glad to solve your problem by using cutting edge methods of ML
Position: Data Scientist
Category: Data Science
Experience: 1.5 years | English: fluent

IBM certified Data Scientist
Currently, I am pursuing a master's degree in Data Science and Business Intelligence at the University of Tulsa. Regarding my practical skills, I completed a variety of projects related to statistical data analysis to tackle real-world problems. My skill set includes experience in Python, SQL, Power BI, R programming, Machine Learning models, academic education, and appliance of data science principles (starting from data engineering to data analysis) and a strong background in programming. I also possess the crucial professional skills of problem-solving, teamwork, organization, flexibility, communication, and integrity which are the fundamentals of a successful career. I am confident in my ability to adapt to the new work environment and be a valuable member of the team of analysts at your company.
These are the Data Science/Analytics related projects that I had involved in:
Project 1:
Examining Sexually Transmitted Infections and Abortion Legalization: Analyzed the impact of different socioeconomic and policy factors on the spread of Sexually Transmitted
Infections (STIs) in 15-19-year-olds. Utilized a bootstrap approach to compare mean estimates and explored Random Forest (r 2 -score = 0.95) and Ridge (r 2 -score = 0.87) regression methods and compared their performances in predicting logged gonorrhea rate for a given population. Utilized R language and libraries of data.table, tidyverse, ggplot2, randomForest, glmnet.

Project 2:
Smart Big Alpha Model: Gathered the stock prices, financial statement & macroeconomic data, technical indicators, and social media sentiment data by using R programming and generated panel data using these data. Tested the big alpha model to analyze the performance & reliability in generating excess returns and achieved a 17.5% return from the portfolio
I am available for an interview at short notice and can be contacted via any of the details below. Thank you for considering my application.
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: intermediate

I have passed the 5 hours Google Tensorflow Developer Certificate exam and achieved my first goal on the way of my Data Science carrier.
I share articles in simple words explaining what I learned on my medium account. After a short period of time I received an offer from the Analytics Vidhya Data Science team to write articles on their blogs.  As writing, sharing is my passion, this was a great accomplishment for me and currently I have two published articles on A.V blogathons.
Currently, I am working as Machine Learning Engineer at A2Z Technologies. Main area of focus includes both NLP models for Speech to Text, Speaker Identification, Speaker Diarization purposes, also Computer Vision projects for face recognition, motion detection, etc. In addition:
Building and optimizing Classic Machine Learning models (Supervised & Unsupervised)
Preprocessing and visualizing data for presentation purposes
Performing statistical testing

In addition, I have worked as Machine Learning Instructor at Tensorflow User Group Azerbaijan for 6 months. I have teached Python, Statistics, Machine Learning, Tensorflow, Deep Learning using Tensorflow framework to group of students. 
Teaching is a great way to both develop yourself and strengthen the knowledge you learn, as well as to be able to benefit enthusiastic young people and give them a chance.
I am a highly organized, motivated, positive, responsible and hardworking worker that ready to help the team to achieve future goals. So, I am expecting the same energy from team.
Position: Data Scientist
Category: Data Science
Experience: 0 years | English: pre

My achievements in my professional activities relate to logistics and sales. You can see my achievements in more detail in my attached resume.
Currently, I have no experience in IT and data science. I decided to change my professional activity from sales and logistics to data science.
You can see my work experience in more detail in my attached resume.
Position: Data Scientist
Category: Data Science
Experience: 0 years | English: upper

I am studying Computer Science at Ukrainian Catholic University. Through my years of studying, I have completed many interesting team projects in the fields of computer vision, image preprocessing, and data science in general. Also, I obtained strong knowledge in parallel computing using CPU cores as well as GPU.
Currently, I have no work experience in the company, however, as a third-year CS student I have completed a lot of team projects as a part of my educational program, as well as various pet projects related to machine learning (deep learning more precisely). The main tools that I use and in which I try to develop, are Python with different libraries for machine learning like PyTorch, Docker, and SQL.
Position: Data Scientist
Category: Data Analyst
Experience: 0.5 years | English: fluent

I've developed and displayed my Car License Plate Recognition project from my internship in Bakutel, which is a technology festival held in Baku. The visitors were really interested in the project.
I've also participated in a competitive programming contest - ACM ICPC and qualified for the regional stage held in Tbilisi. Sadly, I was not able to progress through that stage as the other contestants were quite experienced.
Currently I'm unemployed, looking to learn more skills in my field. I'm studying my 4th year out of 5 in university. Briefly, my skills include:
• Fundamentals and Advanced concepts of the Python programming language;
• Working with Python packages like NumPy, Pandas, Matplotlib, SciPy, etc. to conduct statistical analysis on the data and create visualizations;
• Utilizing the OpenCV package in Python to create Image Processing applications;
• Using different data sources like JSON, SQL Databases and Web APIs;
• Working with statistical functions in Excel and visualizing data;
• Able to develop Object Oriented designs for software systems;
• Can work and communicate effectively alone or with a team;
• Ability to write clean, managable and maintainable code;
• Sufficient knowledge in other programming languages like C/C++, C# and Javascript to interpret the existing code;
• Able to learn to work with new programming languages or softwares in a short period of time.

The work experience that I had was an internship where I built an Image Processing application that identifies license plates of vehicles and applies Optical Character Recognition to convert it into a value and check against a database. During the internship, I've co-operated with two teammates who were responsible for setting up and configuring the hardware and web-design.
I expect a remote job offer that will allow me to improve myself and hone my skills in the field of Data Analysis. I would rather work under a more experienced senior who would direct me in my learning journey and I would be doing tasks which would be of help to them.