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Yurii Data Scientist

Data Science (4.0 yr.), AI and Machine Learning (4.0 yr.)

Summary

- Data Scientist with 4+ years of experience in AI and machine learning;
- Specialized in NLP, time series forecasting, and generative AI;
- Built RAG systems using OpenAI, Langchain, and custom pipelines;
- Developed multi-agent systems for sales enablement, education, and virtual assistants;
- Proficient in Python, SQL, and ML libraries like Pandas, Sklearn, Keras, and PyTorch;
- Created legal assistants with HuggingFace models and citation-based RAG responses;
- Built voice-based chatbots using OpenAI Whisper and ElevenLabs for voice cloning and audio processing;
- Designed pipelines for text-to-speech and image generation in mobile and cloud environments;
- Extracted and analyzed financial data using AWS Textract and OpenAI VLMs;
- Built production-ready support bots using Dialogflow CX, Twilio, and Google Firestore;
- Experienced with AWS and GCP for scalable model deployment.

Work Experience

Data Scientist, Multi-Agent Assistant for Sales Enablement

Duration: 6 months

Summary: Developed a multi-agent assistant for sales enablement, capable of autonomously preparing lead summaries, company/industry reports, and meeting agendas.

Responsibilities:

  • Designed and implemented a multi-agent system that used Tavily API for intelligent web search and synthesis;
  • Automated generation of sales research reports (for person, company, industry) and meeting agendas based on lead data and found information;
  • Built a knowledge base system allowing users to upload files or provide website links for ingestion and querying;
  • Developed a RAG interface to let users interact with their documents and websites in natural language.

Technologies: Python, OpenAI, Tavily, Docling, pgvector, SQL, Langchain.

Data Scientist, Legal Assistant using RAG System

Duration: 3 months

Summary: Legal assistant powered by a RAG system for U.S. constitutional and federal law. Enabled users to ask complex legal questions and receive accurate, citation-based responses grounded in the U.S. Constitution, federal law, and New York State regulations.

Responsibilities:

  • Prepare dataset by parsing and embedding legal documents using text embeddings model;
  • Researched and experimented with different text embedding models from HuggingFace to optimize performance and quality;
  • Implemented a process for intelligent query reformulation step using RAG to improve retrieval accuracy based on the user's intent.

Technologies: Python, HuggingFace, Langchain, OpenAI, AWS.

Data Scientist, Virtual Agent for FAQs and Ticket Logging

Duration: 1 year

Summary: Create a virtual agent for FAQs and logging tickets on TechSupport system. Extract names, mails, phone numbers, issues and details during the conversation fill the ticket on system or send self-guide.

Responsibilities:

  • Design conversational flow and develop a chatbot for realistic conversation;
  • Create a system for managing the connection to the TechSupport system for creating tickets;
  • Extract detailed information from conversation and post-process conversational records and text;
  • Implement issues classification system for smarter assignment of tickets on the TechSupport side;
  • Integrate OpenAI Whisper to improve sound processing.

Technologies: Python, Dialogflow CX, Spacy, NLTK, Twillio, Google Firestore, OpenAI API, GCP.

Data Scientist, DriveED

Duration: 6 months

Summary: Developed a multi-agent generative AI system to automate the creation of lesson plans aligned with U.S. educational standards.

Responsibilities:

  • Designed a modular pipeline for generating lesson plans, integrating curriculum standards, success criteria, and textbook-based task generation;
  • Implemented multi-agent orchestration for concept-based task design, visual asset generation, and final lesson assembly;
  • Tuned agents to adapt lessons by grade level and complexity;
  • Integrated RAG to access relevant textbook content and success criteria dynamically;
  • Contributed to task formatting and refinement to meet pedagogical goals and improve classroom usability.

Technologies: Python, OpenAI, Langchain.

Data Scientist, Interpretr AI 

Duration: 6 months

Summary: A mobile app designed for recording and interpreting users' dreams through a psychoanalytic lens. The bot engages users in interactive discussions to gather insights into their dreams and take into account their life context, aiming to provide meaningful interpretations.

Responsibilities:

  • Crafting a natural dialogue flow to mimic friendly and insightful real-time conversations;
  • Building a system for collecting and analyzing detailed information on dreams, and providing interpretations rooted in Jungian theory;
  • Set Up ElevenLabs with cloning and tuning;
  • Upgrade pipeline for real-time Text to Speech;
  • Integrate Image Generation pipeline with Flux for visualization of Dreams;
  • Image generation with Flux.

Technologies: OpenAI, Flux, Python, ElevenLabs, Grok, Claude, langchain, AWS.

Data Scientist, Tech Cargo System

Duration: 1 year

Summary: The project focused on analyzing and extracting financial information from documents to assess the financial health of companies. Supported multilingual and multi-format document processing.

Responsibilities:

  • Leveraged AWS Textract for automated data extraction from financial documents, including balance sheets, income statements, and cash flow statements;
  • Designed workflows for financial health analysis using custom formulas and algorithms;
  • Integrated OpenAI Visual Language Models for testing advanced data extraction capabilities;
  • Built multilingual pipelines using AWS APIs;
  • Enhanced support for diverse document types, ensuring scalability and robustness.

Technologies: Python, AWS Textract, AWS Textract Queries, OpenAI API (Vision and Text), AWS Translate, AWS Currency Converter.

Education

  • Master of Computer Science
  • Bachelor of Computer Science