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

Aside from thesis, I also participated in different hackathons and scientific conferences during my study. During my last hackathon together with the team, we took prize place, and later the ministry of justice of Ukraine suggested us to work together on the new project. We developed the service for independent anonymous legal polls, that balanced the audience. I engaged in statistics, processed data and made survey reports. After that, with this project we participated in innovation justice challenge 1991, it was like the business incubator. There we improved our skills and got knowledge about the foundation of business startups, and also took prize place.
I want to find something that is connected to data preparation and models training. I am a faculty of CS graduate, and during my study, I also was learning Machine Learning algorithms and methods. I made different pet projects to learn some concepts and wrote machine learning thesis. I researched dependency of some  symptoms and chronic diseases of COVID-19 patients on their disease outcome, who were ill on COVID-19. During my research, I was dealing with medical data, that I was preprocessing, made one-hot encoding and normalization, then trained models for binary classification  (KNN, logistic regression, decision tree classifier, SVM and Naive Bayes) and used metrics, like f-score, log loss and ROC to evaluate the model.
One of the main points in my future work that is weighty for me is that I want to make progress in my developing. So I want to find the project that would be hard enough for me, maybe some technology that I didn’t use in my experience, so I could learn from it and develop my skills. I want to work with machine learning algorithms, and, maybe, with deep learning and neural networks. Also, one of the most important things to me is to have company's values that match my personal ones.  Also I don’t want to work with excel tables.
Position: Data Scientist
Category: Data Science
Experience: 5 years | English: fluent

1. As a pet - project with a student team we have created an interesting app for the Android with cutting-edge AI. search play.google.com for an "Oahega"
or search for the paper in Google:
"OAHEGA: From Research to Production of Mobile Expression Detection Application"
Links are not allowed here.
2. Get used to have prize-winning places in casual hackathons from time to time. 
3. 50 + courses and certificates in AI, DS, ML, DL (majority) and psychology (minority), mainly Coursera.
4. I have trained growing talent in AI and helped for about 10 people to land their job in IT.
I want to spend 50 % of time leading DS / ML team (along with clients communication) plus use other 50 % for the research and tech tasks.

Short experience Looqme:
1. TSA (target dependent sentiment analysis) API. Automation of data labeling for clients ( brand opinion mining). From idea to production.
Technologies and techniques used: Python, Keras, Tensorflow, nltk, scikit-learn, numpy, Fast API, multiprocessing, AWS cloud training, Glove, MLFlow.
2. Role detection API. Detection of target keyword role in text (object, subject, secondary).
3. Explainable AI for TSA. 
Technologies and techniques used: Python, Keras, Tensorflow, nltk, scikit-learn, numpy, multiprocessing, Glove, lime.
4. Monitoring and infrastructure integration for all AI systems.
Technologies and techniques used: Python, Keras, Tensorflow, nltk, scikit-learn, numpy, Fast API, multiprocessing, AWS cloud training, Glove, MLFlow.

Short experience Vimmi:
1. Designed, developed, deployed and tested (recommendation systems) fully automated ML/AI life circle (pipeline) from data to end user along with A/B tests and monitoring. Recommendations power up content engagement of the users and includes: RNN for personal recommendations, NN (related recommendations), contextual bandits, etc.
Technologies and techniques used: Python, Keras, Tensorflow, w2v, scikit-learn, numpy, LSTM.
2. Designed and created analytical system (ELK stack) based on logs from the streaming servers. System processes for about 2+ TB (near 3 Billion events) of information per day and used by people from diverse positions.
Technologies and techniques used: logstash, elasticsearch, kibana.
I want to work on a single product (to be focused on particular tasks in domain). I think there is always room for improvement, thus quality - my philosophy for work and life.
I don't want to urgently and madly solve not DS/AI tasks.
I am interested in new technologies (for example explainable AI), and want to learn new things all the time.
Also I want to lead a team / or at least to coach few middle-junior people.
Position: Data Scientist
Category: Data Science
Experience: 0.5 years | English: upper

I have developed a model capable of finding decay events using the transfer learning approach.

It is noteworthy that the weights that I used for prediction were obtained by training the model on data from a completely different area than the one in which I made predictions.
I was a member of the ALPhA team (Davidson, USA). My work was to develop an unsupervised model that would allow detection of decay events in an AT-TPC detector. The bottom line was to pull our data through the PointNet model (which was trained on completely different data from ours) and extract the latent space from there, which was later used as input data in OneClassSVM.
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: upper

Completed 4 Dataiku Certifications: Core Designer, Advanced Designer, ML Practitioner and ML OPS Practitioner

Completed 3 Kaggle competitions and got 1 bronze medal with a top 6% result.

Had 1 published research paper dedicated to TinyML
I was involved in developing NLP-solution for custom named entity extraction. My goal was to increase baseline performance by redesigning the existing pipeline by adding extra steps of data preprocessing and creating an additional model; I Worked with classification on imbalanced data and a special model for cutting-off major class samples to help the baseline model perform better.

Also, I was partly involved in creating solution for image matching by using different keypoint detection techniques, SIFT and wavelets.

Had a university research project on building IoT hub for a smart house based on Nvidia Jetson Nano and STM32 neuro-controllers. My task was to perform hyperparameter tuning for the LSTM model and optimize the model to be able to program it to the STM32 microcontroller.
More interested in NLP, but open for opportunities in different areas.
I would like to work on interesting and challenging tasks.
Position: Data Scientist
Category: Data Science
Experience: 8 years | English: upper

Age 5 - Space Invaders 9,990 high score all high.
Time series analysis for EEG [for ASD/ADHD] Lead in an interdisciplinary team [anomaly detection, HTM].
Time series analysis for binary trading [algorithmic trading, GAN/CNN/LSTM] 
Economic lead at Aerospace Science Lab [knowledge mining, ESA/NASA/JPL].
Oracle Advanced Analytics implementation for the phytosanitary provisions and systems of the European Union (EU) Cross Border Cooperation Programme [oracle, BI].
Engineering experience in ecologic project www.lucidproject.com  with BCI/AR/VR underwater photography and virtual reality [engineering, C for microcontrollers]
I was involved in writing code that writes code, construction of a huge taxonomy for a specific large-scale project, and jump-starting spin-off.
I am "Data Scientist" more, and less "Data Engineer": it means I understand executive talk and always translated.. also, constantly refine algorithms, do meaningful cross-validation, avoid over-fitting like plague, documenting everything, prioritizing, discussing with stakeholders, planning and testing, testing, testing; always stay on track regarding deliverables and deadlines; managing people, hiring the right people, managing managers; and measuring my ROI was my obsession, and always will be.
I am the best at algorithms, topological data analysis, knowledge mining, predictive analytics, time series analysis, anomaly detection; transfer learning, rapid learning. 
State-of-art projects, storytelling, entrepreneurship, expectation management was my strong sides;
Also in several projects, I was involved in presenting, pitching,  building research teams, mentoring, hiring&leading an international, dense, high-loaded teams.
Would like to be surrounded by professionals who like and care about what they do.
Position: Data Scientist
Category: Data Science
Experience: 0.5 years | English: upper

Completed courses on coursera, solve tasks on Kaggle
I was working during 6 moths, in non-commercial collective.
Position: Data Scientist
Category: Data Science
Experience: 0.5 years | English: pre


I was working on an application for call centers on back-end. During six months in the team, I managed to work on transferring data from S3 to Postgre, as well as adding new features to the project and working on the design of documentation for the project.
Position: Data Scientist
Category: Data Science
Experience: 0.5 years | English: upper

I am just at start of my way in IT industry, was running project on creation of recommender system as described above. 
In previous position (global oil and gas service company), i was managing operations in Ukraine, Hungary, Italy and Israel in person and remotely. Previous employeer provide several courses / schools for development and on each of them i was top performer.
I was working on creation of recommender system for drilling fluid database (oil & gas sector). Also was performing cleaning of database and creating workflow from data to end user.
During project execution was using:
SQL, Python (Pandas, Numpy, Streamlit, Matplotlib, Seaborn), Dataiku, Docker, Azure. Quite a lot of statistics.

Microsoft Power BI Data Analyst Associate (PL-300)
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: intermediate

Education:
NTUU 'Kyiv Polytechnic Institute' (2015-2019) - BS, System Analysis
Ukrainian Catholic University (2019 - 2021) - MS, Data Science
IWIC LLC (3 months)
> Forecasting sales of goods
> Warehouse delivery planning

Stack: Databases (MySQL, MSSQL, MongoDB), Python (numpy, pandas, scikit-learn, lightgbm, statsmodels), flask, github.

The task was to predict sales of different goods for one year.
There were time series analysis and modelling tasks.
The main model was the lgbm regressor; the second model was SARIMAX.
The results of the models were placed on the server using a Flask and Power BI.
Position: Data Scientist
Category: Data Science
Experience: 3 years | English: intermediate


I work as a data scientist for almost four years. 
Also, I am a Ph.D. in mathematics. 
During this time I did different types of tasks. Most of my responsibilities were data analysis, 
data preprocessing, creating, and implementation of models. I worked on tasks with text data, time series, and image data. I used many different libraries such as pandas, numpy, skeat-learn, nltk, statistics, plotly, tensorflow, pytorch and etc.
Position: Data Scientist
Category: Data Science
Experience: 0.5 years | English: fluent

In the area of Data, my biggest accomplishments were finishing my Masters in Data Science and Engineering from Instituto Superior Técnico and developing my thesis. With my thesis I had the opportunity to investigate in the information retrieval area in the clinical/medical domain using state-of-the-art techniques in deep learning and NLP.
I worked 2 years as a backend developer and 2 years as a full stack developer. As a backend developer I worked in a team of web developers in projects to develop websites and web applications. I worked manly with MySQL, and a PHP's framework, Laravel. As a full stack developer I worked in a project where I had to develop an API for managing the CRM and ERP that my company used, Salesforce and SAP Business One. I developed an API using Laravel and worked with Salesforce API and SAP Business One Service Layer. I also developed a back office using Angular.

In 2020 I decided to enroll in a Master Degree in Data Science and Engineering and I graduate in December 2022. I have 6 months of experience as part of the course Applications of Data Science and Engineering for my master's degree. I worked with Centro Hospitalar Universitário de São João's business intelligence team on a project to create a dashboard that monitors the activity of their Pharmacy and Therapeutics Committee, helping them to take valuable insights about their business.

I developed my Master thesis in INESC-ID working in information retrieval. I worked with state-of-the-art techniques in deep learning and NLP, such as BERT.
I am looking for a job as a Data Scientist. I recently graduate from a master degree in Data Science and Engineering and I really want to grow professionally, gain as much experience as I can and learned with more experienced people.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: upper

Master's degree in applied math
Understanding of algorithms and data structures

Courses on:
Python
Machine Learning
Deep Learning

Commercial development
I worked a lot on data preprocessing, model training, CV model construction. I studied Machine Learning at university and created a coursework. In process of learning ML I  have gained experience in data preprocessing, running linear regression, logistic regression, decision trees, random forests models and fine tuning them. Also I have experience in creation and using neural networks. I have developed two pet-projects in Computer Vision with using pre-trained models and transfer learning: 
Tuberculosis detection (accuracy ~85%), 
Cats\Dogs classification (accuracy ~98.5%), GAN to generate anime faces, system to detect is the person on two photos the same, medical image segmentation using U-net architecture.

I have two years of commercial development of ML products for business: AWS recommender system and chargeback/fraud classification system, deploy on AWS using FastAPI.
Experience and career growth.
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: intermediate

Accelerated the work of business processes in the company by 2 times.
I worked as a BI analyst for 1 years, I transferred data from one language to another (MS SQL > MY SQL), created various processes, even drew the design for some website pages in Figme, communicated with customers and developers, compiled TOR.
Position: Data Scientist
Category: Data Science
Experience: 2.5 years | English: upper


I worked as a data analyst in Debt Collection team in bank. I was engaged in time series forecasting, searching for dependencies and correlations in the context of a large amount of data, building and automating reports, customer base segmentation. Also worked in antifraud team where developed multiple rule sets for fraud detection and prevention, completely blocking known fraud schemes, saving up to 65% of potential losses, used machine learning models to identify fraudulent partners
Position: Data Scientist
Category: Data Science
Experience: 1 years | English: fluent


I worked as a scientific consultant in the educational company (Math, Stats). Last year I worked at the position of a researcher in Starcom Worldwide. I prepared data for client teams (Excel, Power BI) and checked data accuracy (Python, Pandas). Now I'd like to focus on DS/ML. So I am looking for an opportunity to dive into the practical application of data science and machine learning. I can speak English, Polish, Ukraine.
Position: Data Scientist
Category: Data Science
Experience: 2.5 years | English: upper


I worked as data scientist and performed tasks such as:
Time-series analysis of stock price movements:
 - building prediction models for intraday trading using machine learning algorithms (boosting models, logistic regression, etc.);
- creation of most indicators and oscillators existed in trading;
- automatic detection of support and resistance levels;
- building OHLC candlestick charts using bokeh;
Analysis of uses' behavior in social discovery company:
- research of the possibility of reducing chargeback rates using machine learning; 
- building predictive models for prediction revenue by users for individual traffic buying channels;
- research on the problem of users’ repurchase and building models for assessing this effect on revenue;
- building a map of transitions of users from various empirical states of a user's life for subsequent testing of hypotheses to improve the current;

Education: Masters' degree in applied mathematics.

Key technical skills:
- programming language: Python;
- visualization tools and libraries: Tableau, bokeh, plotly;
- Python's libraries: numpy, pandas, scipy;
- machine learning and deep learning: lightgbm, scikit-learn, Keras;
- databases and data warehouses: PostgreSQL, MySQL, BigQuery;
- cloud services: AWS;
- OS: Linux, Windows, MacOS;
- knowledge of probability theory and statistics, optimization methods;
Professional data science team, established processes, remote-friendly
Position: Data Scientist
Category: Data Science
Experience: 5 years | English: fluent


I worked at 2 analytics-related internships before and now I work at 

1) Deep Knowledge Group as a Data Scientiest

Finding sources of data and writing scripts for scraping, using APIs
Data processing using Python tools, cleaning, merging, transforming, and populating empty values using external sources
Cross validation of integrity of the data using multiple sources,
including chat bot APIs
Application of Machine Learning (such as classification) and NLP algorithms (such as NER)

2) MKT Production Commercial LLC as a  Risk Data Analyst

Performing a risk assessment: Analysing current risks and identifying potential risks that are affecting the company
Create risk management models for assessing and mitigating various aspects of risk exposure both on Python and Excel
Applying machine learning techniques to financial, sales and
procurement data to improve productivity in terms of time and cost
Preparing monthly reports for the Risk Committee using
combination of MS Excel and visualization tools
Position: Data Scientist
Category: Data Science
Experience: 0.5 years | English: intermediate


I worked for an American company where I developed business logic in Python for a Flask application, utilizing object-oriented programming (OOP) and the pandas library.
Currently, I am developing my skills in deep learning and actively seeking job opportunities in this field.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: upper


I worked for an outsource company for 2 year as a Data Scientist. Experienced implementing different parts of Data Science flow - data cleaning, preprocessing, feature engineering, feature selection, modelling, etc.. Developed recommendation engine, worked in NLP domain and solved Time Series tasks.
Beside that I also experienced integrating all these elements into the web-app and developing business logic of the product.
Would like to concentrate more on modelling tasks and develop my data scientist and quantitative skills.
Position: Data Scientist
Category: Data Science
Experience: 2.5 years | English: fluent


I worked for more than a year as a data scientist (forecasting, A/B tetsing)
with online casino games analytics in a big product IT company. I worked last year as a data scientist  (in particular, a project on 
clustering similar products and detecting anomalies in time series of sales) in a big firm which produces software as a service for retail.

I have a Ph. D. degree in probability theory and mathematical statistics.
I have big experience of working with various classification and regression
 problems (using XGBoost, random forests, generalized additive models etc.) and evaluation of classification performance.  


I would prefer to work remotely.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: fluent

I started my own company from scratch and learned a lot about it, I had 300$ in my pocket and turned them into 15000 in 1 year and a half in a country where inflation is growing everyday (Venezuela).
I worked in Schlumberger in the oil field, in the segment of wireline, which is study of the oil well conditions before/after drilling.
Also was an entrepreneur  of my own Import company of autoparts, named PRIME MOTORS, I sold it.
Currently studying cybersecurity and obtaining Data analysis certification from Google. I want to grow even more in the systems and data management
Position: Data Scientist
Category: Data Science
Experience: 5 years | English: upper


I worked on different projects :

1) Credit Risk Modeling
2) ATM cash optimization 
3) Route optimization

using the following technologies:

1) Cmd scripting
2) R/Python
3) Docker, Git
4) Rest APIs
5) Web Scraping, Automation

Currently I am a team leader in banking sector.
I would like to work on different business problems, particulary time-series cases.
No ML Engineer, Deep Learning.
Position: Data Scientist
Category: Data Analyst
Experience: 0 years | English: intermediate


I worked with regression analysis, classification, clustering, dispersion analysis, built forecast models based on regression models and using MS Excel. To conduct the analyses, I worked directly on cleaning and preparing the data, as well as conducting intelligence and visual analysis for a better understanding of the data. The above-mentioned analyzes were carried out using the programming language P and Python.
Position: Data Scientist
Category: Data Science
Experience: 0.5 years | English: upper

Bachelor's Degree in Process Automation
Currently studying Master's degree in Artificial Intelligence
Work experience as Machine Learning Engineer since 08/2021
I worked with R programming language but I have experience using both R and Python
I worked as Machine learning Engineer Intern but also did some data analysis and data preparation tasks as well.
Position: Data Scientist
Category: Data Science
Experience: 2 years | English: upper


I work in socially important project focused on economics and social developments. 
I am involved in collecting, processing and analysing data in order to do research on its basis. I work with big datasets of numeric and textual data, process them using Python, Pandas, numpy and scikit-learn in particular.
- Developed a system for aggregating articles from the most popular Ukrainian news media websites
- Performed classification, topic modelling and sentiment analysis of news articles in Ukrainian and Russian languages
- Published research articles about job market, hot topics in news, experts in media
- Assisted journalists with data analysis to perform data-driven research
- Organised a workshop to train people basic data collecting techniques with Python and Scrapy
I am interested in projects that help society and concern education, well-being, health, climate action etc.