Welcome to my GitHub! I am a Data Analyst experienced in transforming complex data into actionable insights. I specialize in advanced analytics, machine learning, and data visualization, with a strong background in data engineering. I am passionate about driving business value through data-driven solutions and optimizing strategies for better decision-making.

• 🔭 Currently Working On: Building a Boston city guide using Palantir Foundry, integrating the Ticketmaster API to provide personalized event and activity recommendations through AIP-driven user profiles.
• 📈 Recent Project: Created FoodGenie, an AI-powered recipe planner in Palantir Foundry that analyzes inventory, user mood, and time to suggest meals. Features include a chat assistant, image recognition, and custom AIP logic for dynamic recipe generation.
• 🎓 Education: Master of Science in Information Systems from Northeastern University (2024) and a Bachelor's in Electronics Engineering.
• 🌱 Learning & Interests: Continuously exploring new advancements in data engineering and machine learning.

A Palantir Foundry application that suggests personalized meals based on user inventory, mood, and schedule.

• Integrated 4 object sets and 4 AIP logic blocks for recipe generation, image classification, and Q&A.
• Enabled personalized planning using roommate data and available ingredients.
• Created a chat-based interface for real-time culinary assistance. Explore FoodGenie(https://youtu.be/Cj1Rm57at04)

Built a CRM workflow in Foundry to manage client engagement and automate status tracking.

• Modeled 3 interconnected object sets (Company, People, Engagement) with 10+ validation rules.
• Designed an interactive dashboard with 12+ KPIs and dynamic views across entities.
• Implemented real-time email triggers for all CRUD operations, improving response times by 30%.

Built a conversational analytics tool that bridges the gap between natural language queries and data-driven insights.

• Combined SQL and Python agents to process queries and generate visualizations.
• Incorporated LangChain for contextual query memory and Plotly for interactive visuals.
• Deployed using Streamlit, providing a seamless user interface. Explore QueryLens Code

• Analyzed a dataset of 26 million records using Alteryx and Power BI, providing insights on sales trends and helping drive data-backed business decisions.

• Developed an AI-powered chatbot using GPT-3.5 for tax consultation, achieving a 40% efficiency increase. Integrated Chroma vector databases and a Streamlit UI to enhance user experience. Explore it here.

• Built a scalable voting system using Apache Spark Streaming, Kafka, and Postgres, deployed with Docker for real-time vote aggregation and analysis. View the code here.

• Achieved 95% accuracy using CNNs on a traffic sign recognition project. Explored various ML models and transfer learning techniques to optimize performance.

• Led a team of 6 to analyze Lululemon's stock, improving prediction accuracy by 15% and increasing successful trades by 20%. See the project here .

• Python, SQL, R
• NumPy, Pandas, Scikit-Learn, TensorFlow, Pytorch
• Data Preprocessing & Statistical Analysis

• Tableau, Power BI, Kibana, Excel

• Palantir Foundry, Apache Airflow, Alteryx, SSIS, Apache Kafka, Talend

• AWS, Azure, GCP, Snowflake

• Critical Thinking, Communication, Problem-Solving, Attention to Detail