Data Analyst & AI Engineer

Designed and deployed automated ELT workflows integrating Snowflake, Python, and SQL, significantly improving dataset readiness for visualization and business reporting. Built and maintained ML models for structured and semi-structured datasets using Scikit-learn, statistical modeling, and LLM-based enrichment to derive actionable business insights. Developed intermediate-to-advanced SQL scripts using window functions, CTEs, analytical functions, joins, and subqueries to support analytics workflows and optimize query performance. Designed Power BI dashboards presenting KPIs, trend analyses, and executive summaries, enabling faster decision-making for business stakeholders. Delivered NLP solutions including text classification, sentiment scoring, and named entity extraction using both classical NLP techniques and modern LLMs. Applied Python (Pandas, NumPy) for data cleaning, feature engineering, and API automation, reducing preprocessing time and improving model reliability across projects. Conducted statistical analysis including probability distributions, variance analysis, and hypothesis testing to validate ML model assumptions and interpret outcomes. Participated in data quality assessments and implemented error-checking mechanisms to maintain high integrity across all data pipelines. Managed version control and collaborative development using Git/GitHub, ensuring reproducibility and traceability of all code changes.

Designed and built a real-time behavioral monitoring agent in Python, tracking keyboard timing, mouse dynamics, system activity, and bot-like interactions for risk analysis. Engineered daily and historical behavioral features (typing delay, mouse speed, CPU idle patterns, drift metrics) used as inputs for ML modeling and productivity scoring. Implemented burnout prediction and anomaly detection models using Random Forest Regression and Isolation Forest, including a 30-day trend analyzer identifying rising stress patterns. Built drift detection logic using statistical feature comparisons to measure significant shifts in user behavior over time. Integrated GPT-4 via LangChain for tone analysis, sentiment drift comparison, daily cognitive summaries, and an interactive AI support chatbot. Developed a FastAPI backend serving ML predictions, trend reports, and GenAI insights; built a React dashboard to visualize scores and anomaly alerts in real time. Implemented a full MLOps pipeline with DVC for data versioning, MLflow for experiment tracking, and Docker for containerized deployment across all services. Collaborated on academic research requirements, presenting findings and demo walkthroughs to faculty and peers in both technical and non-technical formats.