Pratap's CV
Pratap Mahalingam
PROFESSIONAL PROFILE
Profile summary
Multilingual professional with 3 years of experience across 5 organizations, bringing GCC experience and cross-cultural team leadership. Skilled in machine learning development, quantitative research, financial modeling, and product management. Delivered machine learning models, integrated diverse incident datasets, and built financial models while applying economic frameworks to complex data. Committed to applying analytical expertise and cross-functional collaboration to deliver data-driven solutions.
Career highlights
Machine Learning Development: Built an end-to-end machine learning system for aviation safety risk prediction using Python, scikit-learn, and pandas on thousands of real incident records.
Quantitative Research: Integrated thousands of breach incidents across multiple independent datasets and applied the Gordon-Loeb economic framework with multivariate regression.
Financial Modeling: Completed a virtual experience involving a three-statement financial model with multi-year projections, company valuation, and pitch book development.
Product Management: Translated business requirements into product documentation, conducted research, mapped user journeys, and supported user experience testing across stakeholders.
Key skills
Professional experience
Developed machine learning systems for aviation safety risk prediction, handling data processing across multiple variables and use cases. Built live deployment infrastructure with interactive dashboards for real time monitoring.
- Built an end to end machine learning system for aviation safety risk prediction using Python, scikit-learn, and pandas.
- Processed 3,000 real incident records across 4 machine learning use cases and 15 variables.
- Achieved 97% recall on the safety critical class.
- Deployed a live REST API with an interactive dashboard for real time risk monitoring.
Conducted independent quantitative research on cybercrime economics. Examined threat intelligence datasets, applied economic frameworks, and executed econometric models to project future breach costs across multiple regulatory scenarios.
- Integrated 22,000+ breach incidents across IBM X-Force, Verizon DBIR, and FBI IC3 datasets with differing schemas.
- Applied the Gordon-Loeb economic framework alongside OLS multivariate regression and ARIMA forecasting through 2029.
Executed financial analysis and strategic modeling workflows, focusing on core banking procedures, enterprise valuation, and transaction analysis.
- Built a 3-statement financial model containing multi-year projections and scenario analysis.
- Executed company valuation and merger and acquisition analysis to support pitch book development.
Executed product management training tasks under supervision, translating business requirements into documentation and coordinating cross-functional collaboration between design, development, and marketing stakeholders.
- Conducted user and competitor research to inform product direction.
- Mapped user journeys and supported UX testing across stakeholders.
- Developed an end-to-end machine learning system in Python using scikit-learn and pandas to analyze 3,000 incident records.
- Built a live REST API with an interactive dashboard for real-time risk monitoring, achieving 97% recall on the safety-critical class.
Education
Aug 2024 – Sep 2026 (Expected)
- Dissertation: The Economics of Cybercrime - 22,000+ incidents across IBM X-Force, Verizon DBIR, FBI IC3; OLS regression and ARIMA forecasting; GCC cybersecurity risk projections through 2029
USA (Online) - Incomplete Fall 2024
- GPA: 4.0/4.0 - Applied Computing in Python (A), Introduction to Health Informatics (A), Security and Privacy (A)
Chennai, India
- CGPA: 7.91/10 | Specialisation: Finance and Business Analytics | Quantitative methods, SPSS
Certifications
Languages
English · Fluent
Tamil · Native
Hindi · Intermediate
French · Basic