About
I am a results-driven Data Analyst who transforms complex, unstructured datasets into actionable business intelligence. Bridging the gap between raw data engineering and executive-level decision-making, I specialize in building end-to-end data pipelines, exploratory data analysis (EDA), and interactive KPI dashboards that drive operational efficiency. With a strong academic foundation in Data Science and hands-on enterprise internship experience, I have a proven track record of optimizing data workflows and delivering measurable business impact. I thrive in collaborative environments where data can be leveraged to solve complex problems and unlock growth. 🌟 KEY HIGHLIGHTS & BUSINESS IMPACT: Data Pipeline Optimization: Streamlined Python preprocessing pipelines, improving data quality and model training throughput by 40%. Business Intelligence: Designed and deployed live monitoring dashboards that reduced manual review times by 30%. Predictive Analytics: Engineered an end-to-end Machine Learning pipeline for employee churn prediction with an 85%+ accuracy rate. Advanced Analytics: Conducted comprehensive customer shopping behavior analysis using statistical modeling across 10,000+ transaction records. Academic Research: Co-authored a published research paper on Smart Agriculture utilizing IoT and Artificial Intelligence. 🛠️ CORE TECHNICAL TOOLKIT: Data Analysis & Analytics: Exploratory Data Analysis (EDA), Statistical Analysis, Data Wrangling, Advanced Excel. Databases & Querying: SQL (Data Extraction, Joins, Aggregations). Programming Languages: Python (Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn). BI & Data Visualization: Microsoft Power BI (DAX, Power Query), Tableau, Streamlit. Data Engineering / ML: ETL Pipelines, KPI Reporting, Logistic Regression, Random Forest, Clustering, Computer Vision (YOLOv8, OpenCV). Tools & Workflows: Git/GitHub, Jupyter Notebook, Google Colab, Roboflow. 👉 Active Pursuit: I am seeking fresher / entry-level opportunities in Data Analytics, Business Analytics, or BI Development across Tech, Consulting, Finance, and E-commerce domains.
Work experience
Data Analyst Intern at SEPIA INNOVATIONS, Apr 2025 - Jul 2025 · 4 mos, •Streamlined data preprocessing and cleaning pipelines in Python (Pandas, NumPy), improving dataset quality and accelerating model training throughput by 40%. •Designed and built a real-time Streamlit monitoring dashboard to visualize telemetry data and anomaly detection logs, successfully reducing manual review time by 30%. •Engineered a Road Anomaly Detection System using YOLOv8 and OpenCV, custom-training models on a self-curated dataset of 2,000+ GPS-tagged and annotated image frames. •Improved model detection accuracy by ~22% through iterative dataset curation, annotation, and retraining cycles on Roboflow to ensure deployment-ready performance. •Collaborated closely with cross-functional teams to document technical findings, translate complex data metrics, and deliver structured performance reports to non-technical stakeholders.
