Danyal Ali Asghar

• Architected an AI-powered lease abstraction platform for life sciences REITs, reducing manual review and
accelerating acquisition and asset management workflows.
• Designed and implemented a multi-parser pipeline (PDFPlumber, Azure Mistral OCR) with dynamic heading
extraction to handle diverse lease formats from biotech and pharma tenants.
• Integrated Azure Mistral and OpenAI for structured extraction, mapping, and metadata, improving abstraction
speed and consistency for commercial lease review.
• Designed scalable Azure-based storage (Blob + Cosmos DB) with multi-tenant isolation and folder conventions
for scanned and processed documents.
• Implemented streaming uploads, progress reporting, and timing metrics across parsing and abstraction to improve
performance monitoring and user feedback.
• Improved reliability with error handling and graceful degradation for non-critical steps in the lease processing
pipeline.
• Built an AI powered lease abstraction system using LLMs for structured data extraction from unstructured legal
documents, improving processing speed and accuracy.
• Developed NLP pipelines and prompt engineering workflows using OpenAI and Azure Mistral for document
understanding and metadata extraction.
• Built a voice assistant prototype using Whisper and GPT for speech to text and conversational AI.
• Designed data validation and monitoring pipelines for AI systems to ensure reliability and performance.

• Built a voice assistant prototype using Whisper STT and GPT-4 for conversational response generation.
• Developed prompt templates and LLM workflows to improve response quality and latency.
• Built APIs and cloud-native services for AI feature integration.
• Designed data validation, monitoring, and automation pipelines in Python.
• Designed and optimized end-to-end ELT pipelines to process multi-source data using Python, SQL, and Airflow/DBT workflows.
• Orchestrated data pipelines using Apache Airflow and automated transformations using DBT for modular, testable data flows.
• Built scalable data models and warehouse schemas in Redshift and PostgreSQL to support analytics dashboards and ad-hoc BI reporting.

• Leveraging expertise in developing modules and JavaScript applications with ReactJS to create data-driven user interfaces.
• Designing and implementing robust back-end APIs to facilitate data integration and analysis.
• Conducting thorough debugging and testing of APIs to ensure data accuracy and reliability.
• Analyzing and transforming existing systems to enhance data workflows and improve efficiency.
• Utilizing PostgreSQL and MySQL for effective data storage and retrieval, optimizing database performance.
• Employing modern build toolchains and package managers (webpack, npm, yarn) to streamline development processes.
• Crafting responsive web applications with HTML, CSS, and Material UI to enhance user experience.
• Collaborating in agile environments using Git and Bitbucket for version control and team coordination.

• Leveraged REST APIs and web scraping techniques to efficiently extract valuable data using tools like Tweepy, Telethon, and GoogleNewsAPI.
• Conducted in-depth sentiment analysis on data stored in MongoDB, utilizing libraries such as TextBlob and VaderSentiment to derive actionable insights.
• Successfully converted NodeJS scripts to Python, enhancing code efficiency and maintainability.
• Executed CRUD operations in MongoDB with PyMongo, ensuring seamless data management and retrieval.
• Proficient in modern build toolchains and package managers, including conda and pip, to streamline project dependencies.
• Automated Python scripts for data fetching, sentiment analysis, and data storage, significantly improving workflow efficiency.