Computational Linguist / NLP Specialist

kyiv, Ukraine · $1500 · 2 years of experience · Advanced/Fluent

Machine learning (sklearn, numpy, pandas + NLP libraries) for text processing and information extraction. Sentiment analysis, emotion detection, grammar correction, etc.

Python, Git, Jira, AWS

Master's degree in NLP from the University of Stuttgart; several Coursera courses, including Andrew Ng's Deep Learning; several completed data science projects.

Team work, exciting tasks, working on a product that people actually use.


Junior Data Scientist

kyiv, Ukraine · $600 · Less than a year of experience · Upper Intermediate

As working experience - my masters work. NLP task, the main task is to summarize the reviews from site - What i've done so far: 1. Data scraping from the site( Used libraries, Requests, BeautifulSoup, headless firefox, etc. And rotation of proxies, user-agents. 2. Cleaned data. 3. Used libraries / approaches - spacy, fasttext / LDA, word2vec, tf-idf. Python (pandas, nympy, sklearn etc.). Databases - MySQL, MongoDb - solved basic tasks as part of university program. Kaggle competitions, at least two. Math / Statistics courses on stepik / edx / coursera, or articles.

Cyber Security, Python, SQL, numpy, pandas, NLP, scikit-learn, MySQL, Machine Learning, Data Mining, Git

Responsible, calm, communicative, team player, strong-willed. Interested in learning new technologies and obtaining new experience. Like to analyze data, participate in Kaggle competitions and learn new information in the fields like: cyber security and data science.

Interesting(complex) tasks. Professional growth, mentor. Awesome working conditions.


QlikView Developer

kyiv, Ukraine · $2500 · 5 years of experience · Intermediate

MySQL, Linux, Oracle, SAP, Nprinting, QlikView Publisher, QlikView Server, QlikView Extensions, ETL

ETL, NPrinting, QlikView Publisher, QlikView Server, MySQL, QlikView Extensions, Linux, Oracle, SAP


Data Scientist

kyiv, Ukraine · $500 · Less than a year of experience · Intermediate

Research and develop models for marketing department Get different data from database using Oracle SQL Make visualizations using power BI

Machine Learning, SQL, scikit-learn, Data Science, Jupyter Notebook, Python, pandas, numpy, Math, Data Mining

My models are used in production

I`d like to share and get experience with new colleagues.


Data Scientist / Data analytics

europe · $3000 · 5 years of experience · Intermediate

WORK EXPERIENCE 09/2018 – Present Data scientist Appodeal Belarus, Minsk Were proposed and adopted a number of changes FFMs, it contributed to the enhancement of the precision model (has been excluded overfitting, auto tuned Hyper parameters); Created new features for FFMs model, which has led to increased accuracy model more than 40%; Has been implemented pipeline for FFM, predicted IMS to CLICKS, CLICKS to INSTALLS, which has led to a great increase in the profit. 09/2017 – Present Data Analyst Playgendary Belarus, Minsk Conducting verification of compliance all in-app monetization events (purchases and subscriptions); Creating reports from RAW data has been located on AWS server (Python + Unix); Organizing process for creating, preprocessing and analysis data collection; Building models (Linear Regression, Logistic Regression) to address business problems (enhancing LTV, players classification); 09/2016 – 09/2017 Data Analyst lifecell Kyiv, Ukraine mobile operator Conducted reports for implementation of marketing strategies LTE, will leading to 18% growth in customer acquisition; Computation customer habits using machine learning package Python Scikit-learn. Carrying out specified data processing and statistical techniques for active subscribers (> 8M); Developing automated process of analysis data implemented on Python; Handling of large datasets stored in relational and non- relational databases (Oracle, MongoDB).

Machine Learning, Python, Data Science, scikit-learn, SQL, pandas, numpy, Math

Data analyst who has been at the forefront of the telecom industry for the past 5 years. Adept of data analysis and visualization data. Specialize in comprehensive automated processing in Machine learning, using huge experience in Python, Scikit-learn, pandas and big data.

16 April

Deep Learning Engineer; Computer Vision Engineer

kyiv, Ukraine · $2500 · 1.5 years of experience · Upper Intermediate

Computer vision: - image classification (Inception, MobileNet, ResNet) - object detection (SSD, RetinaNet, Faster-RCNN) - semantic segmentation (U-Net) - OCR NLP: - text classification Basics: implemented with Python basic ML algorithms: linear and logistic regression, naive bayes, k-means, KNN, PCA, SVM, fully connected neural network Related online courses: - Stanford courses: CS229, CS231n, CS20 - Coursera: Deep Learning specialization, Bayesian methods for Machine Learning

Machine Learning, Deep Learning, Python, PyTorch, Tensorflow, Keras, Math, Data Science, numpy, scikit-learn, pandas, Jupyter Notebook, Algorithms, ensemble neural networks, supervised learning, OpenCV, Jira, SQL, computer vision, Git

16 April

R&D Engineer - Machine Learning | Deep Learning

Remote work, Ukraine · $5000 · 9 years of experience · Advanced/Fluent

Languages: С++, Python, CUDA-C, C#, R (sorted according to the amount of experience in decreasing order). Know, can do (and love to do) everything around Computer Vision, Machine Learning, Deep Learning. I have PhD in Functional Analysis, Master degree in Applied Mathematics.

computer vision, Deep Learning, Machine Learning, С++, CUDA, OpenCV, Python, Git, C#, Jira

In 2010 I've developed a core of content-based image-retrieval engine called WeSEE:Search. When the number of images reached 200 millions I've developed image duplication detection algorithm based on local features. From 2011 till now I develop content-based advertisement targeting solution WeSEE:Ads. It uses images and video from webpage and a lot of Computer Vision algorithms to predict the best possible advertisement. The main technology used is Deep Neural Networks with 15-30 layers for different taks: general categorization, face recognition, age and gender detection, brand-safety. This technology is used by dozen of companies in UK. Currently working for few startups in Israel and USA. I develop Deep Learning systems for them.

I love complex problems :) Interested in Computer Vision, Machine Learning, Deep Learning - everything else won't work out for me.

16 April

Junior Python Developer

kyiv, Ukraine · $600 · Advanced/Fluent

Делал курсовые проекты в универе (написал две игры на С++ с SFML). Много лабораторных работ по основам программирования, ООР, численным методам (численным методам оптимизации), мат статистике и тд (лабы написаны на C++ и Python). Так же проходил онлайн курсы по машинному обучению от МФТИ и оффлайн курсы AI Saturdays от AI Booster.

Python, Machine Learning, numpy, Data Science, Deep Learning, pandas

Разработка собственных игр как курсовых проектов, прохождения онлайн курсов от МФТИ.

Получить крутой опыт, развиться как data scientist / python developer. Готов к фул тайму (иногда с перерывами на универ среди дня на контрольные/ экзамены/ жизненно важные пары, могу отрабатывать позже вечером и на выходных)

16 April

Data Scientist / Data Analyst

Remote work, Ukraine · $600 · 1 year of experience · Upper Intermediate

Front End, RTB/DSP - 1 year Experience with Big Data, Data analysis, have PhD degree in chemistry, study math (linear algebra, etc.)

MySQL, JavaScript, ElasticSearch

Ищу удаленную работу, желательно разовые проекты

15 April

Senior Software Engineer 🔥

eu, scandinavia · $3500 · More than 10 years of experience · Advanced/Fluent

Working in different roles from software developer to team lead, the most part of my career used to spin around C++ exclusively with a good deal of reverse engineering involved, yet for the past 4 years I've been broadening the area of my interests which now includes new tools as well as the entire fields like natural language processing and DSP. Among the various projects I have been involved with there are: - a machine learning model suggesting new words from an article basing on the articles that have been read and thus extending a language learner's vocabulary. The model utilizes word2vec embedded vectors in combination with a traditional binary classifier such as SVM; - a tool with a mixture of technologies within to create encrypted bilingual books for eBook reader. Entailed creation of a javascript component for parallel editing of bilingual texts, along with employment of Haskell Yesod and Electron framework; - a product for media exploitation and forensic analysis of digital devices starting from personal computers to smartphones. Among the distinctive features were pre-configured search profiles, by virtue of which it gained popularity in federal agencies of various countries including U.S. Homeland Security and U.S. Special Operations Command; - a processor module for the popular disassembler/debugger IDA Pro to analyze mCore assembler code of iDEN mobile firmwares from Motorola. The processor module was developed as a part of a bigger reverse engineering project and ultimately its source code was contributed to iDEN hacking community;

C++, STL, Boost, Jira, Git, GTest, gmock, Amazon Web Services, CMake, Python, scikit-learn, gensim, Haskell, haskell stack

In the role of a C++ software developer the biggest achievement has been design and implementation of a versatile device-detecting library - easily configurable, expandable and cross-platform, which beside my own team was adopted by other teams as well. As a team lead, despite taking an active part in kicking off of a completely new team at the new location along with creating continuous integration infrastructure from scratch, I reckon my biggest achievement nonetheless was the high quality of code produced by the team due to utilization of unit testing alongside with automation testing wherever possible. In the role of a reverse engineer the biggest achievement was a 6months+ project on Motorola iDEN mobile phone where I had to learn to extract its data whereas there had not even existed a tool to analyze its firmware. The result improved the marketing value of the product as it became the only one supporting iDENs at the time. Yet it has been long since I did that and have no intentions to get back to reverse engineering. It's here only for the sake of completeness of my previous background. In spite of all stated above, the most recent and the most valuable achievement for me so far has been a machine learning model which will let me finish a piece of software aiming to extend a foreign language learner's vocabulary naturally according to one's reading likings. The model was implemented in Python as a proof-of-concept, evaluated on cross validation/test sets, ultimately the most fit machine learning algorithm was chosen and its parameters adjusted according to the goal.

Having discovered an interest in math, I've decided to do away with reverse engineering, so today I'm more interested in gaining experience in projects with a scientific background.

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