Empowering Intelligent Data Interaction: Build a chatbot-driven SaaS platform with AI-enhanced SQL query generation and predictive analytics.Developed a conversational AI allowing users to interact with the platform through natural language queries and generate SQL queries dynamically.Design and implementation of a data processing module allowing users to upload their data transparently. Developed data cleaning and pre-processing pipelines to ensure high quality input for further analysis.Led the creation of Prophet model within the platform, allowing users to predict future outcomes based on historical data.Design and implement an intuitive analytics dashboard to visualize insights derived from machine learning models.Collaboration with the engineering team to optimize platform performance, ensuring scalability and reliability for a growing user base.

Mission: To revolutionize the Airbnb booking experience through the implementation of advanced data-driven development and improvement of chatbot solutions for internal stakeholders and external customers.Implemented ETL pipelines for seamless integration of booking data from various sources, ensuring accuracy and consistency.Using machine learning models to predict demand and optimize pricing strategies.Implemented machine learning models to improve chatbot accuracy for customers.Created a real-time data streaming architecture based on Kafka for instant updates on property availability.Automating the deployment and integration of Docker images using a CI/CD pipeline

implementing an internal chatbot using Rasa NLU for natural language understanding.Fine-tuning the BERT model using internal company data to improve its understanding of employee requestsChatbot integration with internal databases and APIs, enabling seamless information retrieval and task automation for company employees.Deployment on the AWS environment (EC2, S3, Glue, Athena...)

Develop and deploy an advanced recommendation system integrated with AI-driven product search optimization to enhance user experience and drive sales on the e-commerce platform.Collect user browsing history, purchase behavior, product attributes, and search queries.Integrate data from various sources using Python, SQL, and ETL tools.Engineer user preferences, item embeddings, and contextual information.Design and implement recommendation algorithms (collaborative filtering, content-based filtering, hybrids) using TensorFlow and scikit-learn.Integrate advanced techniques like attention mechanisms and reinforcement learning.Develop AI-driven search algorithms using NLP and deep learning techniques.Build scalable search indexes with Elasticsearch or Apache Solr.Key Technologies: Python, TensorFlow, scikit-learn, Elasticsearch, Apache Solr, NLP, Docker, AWS/GCP, CI/CD, Git.

Mission: Revolutionize appointment booking processes with data-driven solutions.Developed ETL pipelines to seamlessly integrate appointment data from various sources, including online booking platforms, phone calls, and in-person registrations.Design and implementation of dynamic scheduling algorithms that take into account factors such as physician availability, treatment duration, and patient preferences.Built-in machine learning models to predict appointment demand, enabling proactive schedule adjustments to optimize clinic resources.Established real-time pipelines for instant appointment availability updates to enhance patient engagement.