Lalithya Kalluri

Data Analyst with 3+ years of experience leveraging SQL, Python, and data visualization tools to deliver actionable insights and support business decision-making. Skilled in developing dashboards, streamlining ETL pipelines, and analyzing large datasets across fintech, IoT, and operations analytics. Strong background in translating complex data into clear, data-driven stories for stakeholders. Adept at collaborating with cross-functional teams in Agile environments to optimize reporting and forecasting processes, with growing expertise in supply chain and operations analytics.

Microsoft Certified – Azure Data Fundamentals

Inventory Demand Forecasting, Python, Power BI, Built predictive models using time-series forecasting and regression techniques to anticipate product demand; improved forecast accuracy by 20%, reducing stockouts and excess inventory. Logistics Optimization, SQL, Tableau, Analyzed shipment and delivery datasets to identify bottlenecks and optimize routing; reduced delivery delays by 15% while improving on-time fulfillment. Procurement Spend Analysis, SQL, Excel, Tableau, Developed dashboards to track supplier performance, purchase order trends, and cost variances, enabling procurement teams to negotiate better contracts and achieve cost savings.

[GitHub/Portfolio]

• Customer Churn Prediction, Python, Power BI, Built classification models (Logistic Regression, Random Forest) to predict churn and designed dashboards, improving customer retention insights by 30%.
• 911 Call Service Analysis, PySpark, Spark SQL, Conducted EDA and classification to identify high-priority emergency calls, boosting response accuracy by 40%.
• Renewable Energy Grid Optimization, ML, Applied forecasting models to predict energy loads and improve grid stability using real-time datasets.