Vinamra Rai Email & Phone Number

Cleveland, Ohio, United States

– Developed Volatility forecasting models leveraging return and infrastructure metadata, enabling more accurate risk management and pricing strategies– Validated Infrastructure Mosaic scoring system by analyzing 10+ years of amber asset returns, demonstrating ~80% explanatory power through machine learning and identifying significant positive correlations (p<0.05) with risk-adjusted performance metrics– Implemented a quantitative framework analyzing 141 short-WALT assets, revealing an 84% renewal success rate and a 17.13% average performance improvement, driving risk-adjusted return optimization and uncovering significant mispricing opportunities– Secured a full-time return offer

Mumbai, Maharashtra, India

– Collaborated with wealth managers and risk management professionals by leveraging Aladdin to address investment requirements and implement comprehensive factor-wise risk reporting– Spearheaded technical implementation for a major South African investment firm, successfully delivering the team’s inaugural client engagement from Africa

Mumbai, Maharashtra, India

– Automated implicit diversification calculation, yielding a 98% reduction in runtime for enhanced efficiency– Devised a comprehensive suitability framework to screen thousands of investment proposals on a daily basis, incorporating volatility, concentration, and cost-benefit checks against clients’ existing portfolios– Led the effort to develop a scalable script to compute the direct/indirect exposure of all EMEA portfolios to Russian and Ukrainian securities during military escalation, assisting clients in a timely rebalancing of models and portfolios

– Classified images of highway intersection and exits into High, Medium and Low based on accident proneness– Implemented Transfer Learning using ResNet50 model using Keras 2.0 framework for feature extraction– Accessed Google Maps API and HSIS (USA) to extract Satellite Images and Average Annual Traffic Data– Analyzed 1000+ images of highway intersections with data augmentation techniques to build a robust model– Utilized Google Maps and ML methods to construct a model having a global application contrary to previous research

Ahmedabad, Gujarat, India

– Structured and analyzed Census-2011 data to study the work commute and travel behavior of people across India, district-wise.– Analyzed the overnight travel data from NSSO's 72nd Round of Survey to explore the district-wise medical tourism trends across India.– Assisted in the conduction of the National Capital Region Survey to determine the modal choice of the working population. – Used R and Stata for data analysis and structuring, respectively.

Master'S Degree, Financial Engineering, 3.93/4.0

Activities and Societies: Fink Quantitative Finance Fellow Vice President of CareersFirst Place at the Thirteenth Annual IAQF Research.

Btech In Civil Engineering; Minor In English Literature

Activities and Societies: Coordinator, Quiz Club (2018-19)

Intermediate, 95.8%

Activities and Societies: Quiz Club President