Team Lead2018 - 2019The National Academy of Sciences of Ukraine
Technologies: Python, Keras, TensorFlow, PyTorch, OpenCV
- Led and mentored a team of students. I defined objectives, and controlled the process using the Agile methodology.
- Created a tool for crops classification and map creation.
- Collected data both manually, and via web scraping using Mapillary, and oversaw the data labeling.
- Implemented and tested DeblurGAN, as well as several other classic deblurring methods.
- Oversaw field localization (YOLO), and crop classification by fine-tuning a ResNet model.
Senior Data Scientist2017 - 2019Openwave Mobility
Technologies: Python, C++
- Created a multi-staged data pipeline from raw packets data (TCP/IP layer) to consumable inputs for machine learning models with multi-processing implementation in Python (CPython).
- Trained, tuned, evaluated and compared multiple machine learning models in Python (scikit-learn, Keras, XGBoost, CatBoost) and C++ (mlpack).
- Oversaw the data analysis and communication with stakeholders. Created a reusable Python tool for rapid and externally configurable data analysis reports generation.
- Implemented custom feature generation algorithms based on expert knowledge based on aggregation, derivatives, delays in TCP/IP conversation, products, and fractions.
- Implemented custom multi-staged feature selection algorithms that were model based.
- Deployed and monitored the project in production in the network. If the tool detects congestion, optimization policies were applied. Customers reported up to a 20% increase of quality of delivery for video content.
Data Scientist2015 - 2017Octetis
Technologies: Python, Keras, TensorFlow
- Developed, deployed, and evaluated a hybrid recommendation engine in Python for an online store.
- Oversaw customer behavior analysis, visualization, and stakeholder communication.
- Handled different scenarios of user engagement using a strategy pattern. Contextual recommendations were given based on popularity (general and category-based), item-to-item, and SVD. (Python, scikit-learn, SciPy). The system was integrated into a Django website.
- Conducted multiple A/B tests with random sampling for evaluation of the system. Compared to the most popular items in the category baseline, we achieved up to a 150% boost in purchases-per-session, and increase of revenue.
- Created an image super-resolution module for an online Cloud site constructor with Keras.
- Utilized middle-deep CNN, trained on several blur kernels, and deployed it as a service via REST.
- Conducted surveys showing an increase of about 5% in the satisfaction for users of the platform.
Software Engineer Intern2015 - 2015
Technologies: Python, Hive
- Trained and evaluated AdaBoost models for customer churn prediction using FBLearner Flow.
- Performed hyperparameters tuning.
- Data engineered with Hive, and processed data using Python.
Researcher Intern2014 - 2015Samsung
Technologies: Java, Android, C++
- Developed algorithms for smart keyboard functionality (word prediction and spelling correction).
- Developed Naive Bayes for n-grams, and K-Nearest Neighbors (KNN) for spelling corrections.
- Created tweaks for better algorithm performance using Laplace smoothing, and a custom keyboard distance for KNN.
- Developed algorithms with C++. Integrated them with a Java to Android keyboard and published to the AppStore.
Software Engineer Intern2013 - 2014Engage Point
Technologies: Java EE
- Developed a Content Management Interoperability System in Java EE. I used the Model View Controller framework for the application.
- Developed Enterprise Java Beans for the business logic of the application.
- Developed JavaServer Pages for the presentation level.