Professional Journey

📝 Led a 5-member team in the design and development of MindMate AI, an AI-powered mental health triage and decision-support assistant built for the IBM TechXchange Hackathon.

Oversaw end-to-end system development, including data preparation, prompt engineering, agent logic design, and integration of model outputs into a user-centered interface.

Focused on explainability, responsible AI principles, and real-world applicability, translating structured patient inputs into clear, actionable recommendations under tight delivery timelines.

📝 Data Management Intern supporting donor and stakeholder reporting through data collection, cleaning, and analysis. Created and maintained Excel and Power BI dashboards to track program performance, efficiency, and key development indicators. Assisted with data quality checks, documentation of reporting processes, and alignment of datasets with global development standards to ensure consistent and reliable reporting.

📝 Contributing as an Applied Data Scientist with the National Student Data Corps (NSDC), working on multiple real-world data science and AI projects in the public sector.

Projects are assigned and delivered on a rolling basis, including traffic safety analytics, healthcare data analysis, and applied AI systems.

Current and completed work includes:
• Accident hotspot analysis using real-world transportation and incident data
• Development of an AI-driven medical chatbot for health information and decision support
• Ongoing applied data science projects supporting public-sector and healthcare use cases

Focus areas include data cleaning, exploratory analysis, feature engineering, model-driven insights, and responsible AI, with an emphasis on real-world impact, transparency, and interpretability.

📝 Data Analyst responsible for developing and maintaining analytical reports and dashboards using Excel and Power BI to support donors and organizational stakeholders. Analyzed operational and development data to track performance, efficiency, and key indicators. Ensured data quality, standardized reporting processes, and documented workflows to enable consistent, accurate, and data-driven decision-making.