Reshma Manjunatha Rao

1) Built interactive Excel and Tableau dashboards to visualize downtime and operational inefficiencies. 2) Applied SQL to classify datasets and highlight anomalies, simulating operational risk assessment. 3) Gained exposure to consulting workflows and client-oriented reporting.

• Reduced manual data processing overhead by 60%+ by designing and implementing automated Python and shell-scripting pipelines for large-scale numerical simulation datasets. • Performed systematic root cause analysis on convergence failures and instability in iterative model runs, by monitoring parametric output trends. • Improved model accuracy by ~5% through structured parametric data optimisation and multi-stage validation checks.

1) Modeled physical parameters of 30+ systems using statistical analysis and FORTRAN-based codes. 2) Assisted in the analysis of >100k simulation outputs, detecting rare anomalies in noisy datasets. 3) Conducted quantitative spectral data analysis, reducing model-data mismatch by 20%. 4) Developed experience in extracting trends from complex numerical datasets. 5) Presented results in seminars, translating complex data into clear insights for non-technical audiences.

1) Conducted market research to identify trends in corporate training and align offerings with industry demand. 2) Collected and analyzed client data from 50+ companies, producing actionable insights for decision- making. 3) Designed and implemented KPI tracking and Excel-based reporting to evaluate sales performance. 4) Presented recommendations to non-technical stakeholders, increasing lead-to-client conversion by 15%.

Master’s thesis: Focus on numerical modeling and large-scale data analysis (Grade: 1.3)