Arushi Srivastava
Hi, I’m Arushi! I currently work as a Trading Analyst at LMCG Investments, a $5B structured credit hedge fund, where I architect algorithms and build analytical frameworks that help shape investment decisions. I love the intellectual puzzle of markets - finding signal in noise, translating messy data into conviction, and figuring out how capital actually moves through the economy.
I graduated from the University of Pennsylvania in 2024 with a B.S.E in Computer Science and minors in Economics and Data Science. During my time at Penn, I was a teaching assistant for an Intro CS course, wrote for the Daily Pennsylvanian, and was a member of Theta Tau, Penn’s engineering fraternity.
In my free time, I’m hunting down the best coffee shops in NYC, sweating in my hot yoga class, or experimenting in the kitchen (with occasional success). I created this space to document what I’m building, share thoughts on markets and investing, and publish the occasional opinionated take. Coffee recommendations always welcome at arushi.mail16@gmail.com.
Experience
Trading Analyst LMCG Investments
- Optimized fixed income and multi-asset trade execution workflows using Python and SQL across 100M+ record datasets, enhancing strategy performance and alpha generation by 30%
- Built automated investment data pipelines monitoring credit and bond exposures, improving strategy responsiveness to spread and rate signals
- Contribute to strategic discussions for a $5bn fund as part of the 7-person investment team, integrating quantitative and credit risk insights into portfolio construction
Financial Engineering Summer Analyst BlackRock
- Stress-tested a new risk analytics server using Python statistical models, contributing to department-wide adoption and enhanced multi-asset portfolio risk monitoring
- Developed portfolio performance toolkit using the Tableau API, Python, and SQL, streamlining benchmarking and monitoring workflows
Data Science Intern Fidelity Investments
- Built machine learning models using PCA and K-Means Clustering to detect bond pricing anomalies with 80% precision, enabling early identification of mispricings and credit risk signals
- Automated data pipelines enhancing bond pricing accuracy and accelerating integration into credit portfolio analytics
Teaching Assistant University of Pennsylvania
- Taught core CS concepts including algorithmic complexity and data structures, held office hours, and graded weekly homeworks and exams for over 200 students
Education
University of Pennsylvania
B.S.E. in Computer Science, Minor in Economics & Data Science
- Grace Hopper Conference Scholarship, Benjamin Franklin Scholar
- Relevant Coursework: Corporate Finance, Statistics and Probability for Data Science, Machine Learning and AI, Mathematical Fundamentals of Linear Algebra and Optimization, Big Data Analytics, Macro-Modeling Economics
Leadership
Board & Project Member Women in CS
- Organized an annual all-woman hackathon with 250+ attendees, fostering innovation and technical education in the Philadelphia tech community
- Built predictive analytics models using Python to forecast content engagement trends in TED talks and applied NLP techniques to analyze 100,000+ COVID-related tweets for sentiment trends
Webmaster Upenn Theta Tau
- Designed and maintained website analytics dashboards and blogs for 100+ users, improving engagement and accessibility