Computer Science & Mathematics
NandanSensarma
Quantitative researcher and data engineer exploring the intersection of technology, finance, and analytics
About Me
Bridging Numbers & Narrative
I'm a sophomore at Penn State pursuing dual degrees in Computer Science and Mathematics with a minor in Economics. My academic journey is driven by a fascination with how quantitative methods can unlock insights in complex systems—from financial markets to strategic decision-making.
Currently, I'm working as a Strategy Intern at Doosan Bobcat building data pipelines and competitive intelligence tools, while also conducting quantitative research with Wall Street Quants developing systematic trading models.
Beyond the classroom and workplace, I lead Penn State's Rifle Shooting Club as President, co-founded the FinTech Group's technology initiatives, and work as a Resident Assistant fostering community on campus.
When I'm not coding or analyzing data:
Experience
Where I've Made Impact
Doosan Bobcat North America
CurrentStrategy Intern
May 2025 – Dec 2025
Statesville, NC
54K+
ZIP-level observations scraped across 23 manufacturer sites
2,200+
Dealer locations analyzed for spatial coverage gaps
35K+
Data points per coverage map visualization
350+
U.S. data center operators analyzed for market strategy
- Engineered large-scale data pipelines for competitive intelligence
- Built dashboards surfacing territory inefficiencies across product lines
- Designed layered spatial models in Excel for coverage visualization
Wall Street Quants
Quantitative Researcher
Jul 2025 – Sep 2025
Remote
1.57
Sharpe ratio achieved (net, 3-day holding)
1,000
Equities in cross-sectional momentum models
- Built systematic momentum models across 1,000 equities
- Engineered standardized intraday price datasets for factor research
- Developed ML models using MLflow for reproducible research
- Evaluated strategy robustness across volatility regimes
Red Cell Analytics x PaCIC
Primary Research Assistant
Nov 2024 – Apr 2025
State College, PA
7
Decision-making simulation scenarios designed
12
Layered red team simulations executed
- Assessed threat scenarios including FIFA World Cup 2026 using OSINT
- Designed simulations emphasizing adversarial planning
- Modeled high-impact decision-making under uncertainty
Skills
Technical Arsenal
Languages
Data & ML
Tools & Platforms
Certifications
Awards
Projects
Featured Work
Penn State FinTech Group
FTG 40 Index
Led development of PSU's FTG 40 Index that outperformed S&P 500, automating portfolio tracking and reducing manual effort by 70%.
Outperformed
S&P 500
Manual Effort
-70%
Wall Street Quants
Cross-Sectional Momentum Models
Built systematic momentum models across 1,000 equities achieving 1.57 Sharpe ratio. Engineered standardized datasets for factor research and ML-based signal development.
Sharpe Ratio
1.57
Equities
1,000
Doosan Bobcat
Competitive Intelligence Platform
Engineered large-scale data pipelines scraping 54K+ ZIP-level observations. Built dashboards surfacing territory inefficiencies and distribution asymmetries.
Data Points
54K+
Manufacturers
23
Red Cell Analytics x PaCIC
Threat Assessment Simulations
Designed decision-making simulation scenarios for strategy team exercises. Executed layered red team simulations modeling high-impact decisions under uncertainty.
Simulations
12
Scenarios
7
Education
Academic Foundation
The Pennsylvania State University
University Park, PA
Expected May 2028
CGPA: 3.97/4.00
College of Engineering
B.S. Computer Science
Eberly College of Sciences
B.S. Mathematics
Minor: Economics
Relevant Coursework
Leadership
President
Oct 2024 – PresentPenn State Rifle Shooting Club
Leading 35 members, managing $7K budget
Technology & Innovation Head
Mar 2025 – PresentPenn State FinTech Group
Founding member, built FTG 40 Index
Resident Assistant
Aug 2025 – PresentPenn State Residence Life
Mentoring 36 residents, 25+ events/semester
Contact
Let's Build Something Together
Whether you're looking for a quantitative researcher, data engineer, or just want to chat about markets, technology, or Arsenal's latest match — I'd love to connect.
Send me an email