Bohdan – Deep Learning, Data Science, NLP

B2B ad tech project, mostly focused on real-time bidding models and NLP-based ad campaign ranking system with millions of daily queries and managing/monitoring available ad inventory.

• Developed ad campaign/website ranking system using the latest NLP models for millions of websites and thousands of campaigns daily, optimized storage costs, and employed heuristics and algorithmic optimization
• Developed model monitoring tools, dashboards, and back-testing instruments
• Conducted A/B testing of RTB models and different features
• Reduced bot traffic by 1.5%
• Took part in GPT-3/4/J, Chat-GPT POC development

Internal securities data provider with conversational AI capable of text2code generation (including complex aggregate requests), basic dialogue capabilities, embedding-based search engine, and a recommender system.

• Developed hybrid approach search engines/content-based recommendation systems, measured model effectiveness, beating Elastic Search nDCG score by 70%
• Developed conversational AI models capable of translating user utterances into SQL/NoSQL requests
• Created synthetic datasets from scratch, used data augmentation techniques
• Took part in speech recognition R&D
• Fine-tuned BERT-based NLP models to specific domains

Open source python clustering library.

• Was in charge of a visualization task of genetic algorithm clustering during his own research
• Used PyClustering as an open-source library, however during his experiments he noticed incorrect crossover mask generation and certain issues with constructor parameters
• Fixed the bug with mask generation
• Slightly refactored the constructor so it was able to have the required parameters passed correctly
• The changes were introduced manually in PR #474

An AI start-up is trying to monetize ML in every conceivable way. From predicting sports outcomes and tracking players from video feeds to reinforcement learning trading agents.

• Created a sports outcome prediction model and paired it with a profitable bet allocation strategy
• Took part in the development of tracking through detection model (background subtraction + Kalman filter) for football player analysis, optimized reading stream, improved FPS throughput from 30 to 45 fps
• Developed several Q-learning-based trading agents, beating the annual return benchmark by 1.5%

IP telephony/B2C ads focused CRM with Google analytics/social media integration and basic conversion outcome predictive models.

• Was responsible for REST API development
• Was in charge of oAuth2.0 integration
• Prototyped and integrated a regression model for conversion modeling using Accord.Net
• Created clustering based on client website activity
• Integrated speech-to-text translation of recorded phone calls into the CRM using Google Speech API