Lasya Nandini — Software Engineer

I work in the Aerospace & Defense domain, where I contributed to building an end-to-end forecasting pipeline used to predict part-level demand for Boeing’s global supply chain. My role involved transforming raw ERP data into forecast-ready time-series datasets inside JDA, enabling automated forecasting using statistical and machine-learning models such as Moving Average, Holt-Winters, ARIMA, and Croston’s method. The forecasting system now produces reliable 24-month demand projections, helping the business make proactive decisions around procurement, warehouse stocking, and inventory planning. A key part of my contribution included: ▪️ Designing ETL logic using SQL & PL/SQL to convert transactional ERP data into structured forecasting datasets ▪️ Developing processing logic for business rules, historical alignment, and forecast preparation ▪️ Implementing quality checks to ensure forecast inputs were accurate, complete, and consistent ▪️ Structuring historical and current demand signals into schemas compatible with JDA’s statistical engines ▪️ Automating forecasting execution through scheduled batch runs across daily, weekly, and monthly cycles Once deployed, I continued to support the pipeline by monitoring execution, analyzing forecast accuracy, resolving data discrepancies, and collaborating with planning teams to interpret outcomes and drive improvements.

Stackforce AI infers this person is a Data Analyst specializing in Aerospace & Defense supply chain forecasting.

Location: Chennai, Tamil Nadu, India

Experience: 2 yrs 6 mos