Lead Data Scientist2020 - 2021Botprise, Inc.
Technologies: Amazon Web Services (AWS), Python, Flask, MongoDB, Apache Kafka, React Redux, REST
- Developed back end for full ML cycle (ModelOps and MLOps) on the platform.
- Worked on dozens of automation use cases, including MLOps, analytics, DataOps, networks, ITOps, and more.
- Created back end and partially front end (React) for drag-n-drop chatbot building application.
- Implemented and deployed several dozens of different algorithms (classification, clustering, time series, NLP, computer vision) for different use cases.
- Led small ML team (planning, management, monitoring, leadership).
Senior AI Developer2019 - 2020Akcellita
Technologies: Amazon Web Services (AWS), AWS, TensorFlow, Python
- Developed an ingestion and processing pipeline on AWS for photos from surveillance cameras.
- Experimented with various non-DL and DL approaches and tested them. Trained and used the Siamese Network with an attention mechanism, achieving 95%+ accuracy.
- Created and shared presentations with analytics to executives. Developed and maintained a Wiki for the project.
Team Lead2018 - 2019The National Academy of Sciences of Ukraine
Technologies: OpenCV, PyTorch, TensorFlow, Keras, Python
- 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 and several other classic deblurring methods.
- Oversaw field localization (YOLO) and crop classification by fine-tuning a ResNet model.
Senior Data Scientist2017 - 2019Openwave Mobility
Technologies: C++, Python
- 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: TensorFlow, Keras, Python
- 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: Apache Hive, Python
- Trained and evaluated AdaBoost models for customer churn prediction using FBLearner Flow.
- Performed hyper-parameters tuning for optimization.
- Data engineered with Hive and processed data using Python.
Researcher Intern2014 - 2015Samsung
Technologies: C++, Android, Java
- 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 App Store.
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.