Andrii – Python, NumPy, PyTorch

A generative AI-based solution for efficient and accurate search of healthcare documents, utilizing advanced LLM models, document metadata, and ICD codes.

• Designed the architecture for integrating LLMs, document metadata, and ICD codes to enable efficient and accurate document retrieval.
• Guided the selection, fine-tuning, and deployment of generative AI models to optimize search relevance and performance.
• Ensured the system could handle large volumes of healthcare documents while maintaining high search speed and accuracy.
• Implemented best practices for data privacy, security, and regulatory compliance (e.g., HIPAA, GDPR) in handling healthcare data.
• Worked with data scientists, engineers, and healthcare professionals to align technical implementation with real-world medical use cases.

OpenAI-based solution for providing assistance to customers by answering their questions and creating, supporting, or processing tickets.

• Designed the overall system architecture, integrating OpenAI-based models for answering customer queries and handling ticket processing efficiently.
• Guided the engineering team in implementing core functionalities, ensuring best coding practices, and overseeing the deployment of the system.
• Integrated AI-powered natural language processing (NLP) models to improve response accuracy and optimized performance for real-time customer interactions.
• Coordinated with product managers, customer support teams, and business stakeholders to define requirements and align the system with business needs.
• Implemented robust security measures to protect customer data and designed the system for scalability to handle increasing support requests efficiently.

The solution systematically examines incoming images, employing a nuanced analysis to generate novel visual representations in accordance with predetermined business rules and prompts. This intricate process involves not only the interpretation of image content, but also the transformation of said content into meaningful representations that align with the specified criteria.

Among others, Andrii managed the following tasks:

• Led the development and implementation of data-driven solutions;
• Architected and managed scalable data pipelines;
• Managed a team of data scientists, analysts, and engineers;
• Mentored and coached junior data scientists;
• Presented technical findings and recommendations to stakeholders.

The OpenAI-based solution is meticulously crafted to deliver comprehensive assistance to customers, proficiently addressing their inquiries and proficiently generating, supporting, or processing tickets. This advanced system employs sophisticated natural language processing techniques to not only comprehend customer queries, but also execute efficient ticket management, thereby enhancing the overall customer support experience.

The challenges Andrii satisfied:

• Orchestrated the architecture of client and manager web applications, with a focus on data science and natural language processing elements;
• Ensured a robust codebase by emphasizing data science and natural language processing functionalities;
• Conducted thorough code reviews with a specific emphasis on data science and NLP components;
• Assumed key responsibilities as a code owner, with a particular focus on overseeing data science and NLP-related aspects of the codebase.

The advanced solution systematically scrutinizes real-time activities performed by website visitors, utilizing sophisticated analytical methodologies to identify intricate patterns. This capability enables the system to proficiently categorize visitors into distinct clusters, establishing a foundation for comprehensive analysis and the implementation of targeted follow-up strategies. Consequently, this approach optimizes the overall comprehension and engagement with the user base.

Andrii successfully carried out the following responsibilities:

• Implemented advanced statistical, mathematical, and machine learning procedures to extract actionable insights from diverse datasets;
• Conducted rigorous cross-validation of models to ensure their generalizability and robust performance;
• Collaborated with interdisciplinary teams to define and refine project objectives, integrating statistical methodologies for data-driven decision-making;
• Developed and optimized algorithms to address complex data challenges and improve predictive modeling accuracy;
• Contributed to continuous improvement by staying abreast of the latest advancements in statistical and machine learning methodologies.

The system systematically identifies and ranks leads of utmost importance, potentially bearing profitability, at each stage of the Sales Funnel. Employing sophisticated algorithms and analytical methodologies, it not only prioritizes leads, but also furnishes the sales team with insightful information. This contribution aids in strategic decision-making, thereby optimizing lead management efficacy.

Andrii achieved the following:

• Identified relevant data sources for business needs, collecting both structured and unstructured data;
• Sourced missing data and organized datasets into usable formats to facilitate analysis;
• Built predictive models and implemented machine learning algorithms to extract valuable insights;
• Enhanced the data collection process to optimize efficiency and accuracy;
• Contributed to the improvement of overall data quality and usability through systematic data organization and model building.