• Developed 30+ automated web scraping solutions, providing 100k+ data records from court websites everyday. • Designed and deployed the data pipeline and automation flow using Apache Airflow, reducing data processing time by 50%. • Developed scalable APIs using FastAPI framework for customer consultant website, processing 20k+ requests per hour. • Contributed to data analysis system utilizing LLMs, providing 10+ new insights of user requests and increasing the winning rate by 10%.

• Implemented a facial recognition system using deep learning frameworks such as OpenCV and TensorFlow, achieving a recognition accuracy of 98%, enhancing security measures and streamlining access control processes. • Contributed to a Healthcare Chatbot solution leveraging OpenAI GPT-4, LangChain and Pinecone, resulting in 40% user engagement increasement. • Combined legacy automation tools with CV technologies like OCR and Object Detection for document processing, increased processing time by 80% ensuring 90% accuracy. • Developed various medical record analysis systems, generating new insights of medical records and enhancing the chatbot's knowledge base by 20%.

• Developed and implemented Python-based web scraping scripts using libraries such as BeautifulSoup and Selenium, extracting over 1 million data points per day from various sources, resulting in a 60% increase in data availability for analysis. • Utilized advanced algorithmic optimizations and parallel processing techniques with celery to process large datasets, reducing computation time by 60% and enabling real-time data analysis for improved decision-making. • Implemented advanced data cleaning and preprocessing techniques using Pandas and NumPy, resulting in a 30% reduction in data errors and inconsistencies. • Designed and implemented automated data visualization dashboards using Python libraries such as matplotlib and seaborn, providing stakeholders with real-time insights and reducing reporting time by 50%.

• Successfully implemented a microservices architecture using Python and Flask, resulting in a 50% reduction in response time and improved scalability for handling over 100,000 concurrent requests. • Developed and integrated a robust caching mechanism using Redis, resulting in a 70% reduction in database queries and a 30% improvement in application response time. • Collaborated with a cross-functional team to integrate third-party APIs, such as payment gateways and social media platforms, into the backend system, enhancing functionality and driving a 25% increase in user engagement, ultimately boosting sales conversion rates and revenue growth.