BSc Economics & Finance candidate at Ashoka University with a CS minor. I turn messy data into research, financial models, and civic tech, from tax policy to stock screening to solving problems.
Three projects spanning applied policy research, quantitative finance, and civic tech built for real users across India and East Africa.
Personal Project · Jan 2026
A web platform combining Reddit-style discussion with GitHub-style solution tracking, where students across East Africa post local problems, then browse and adapt solutions that already exist elsewhere in the world.
Ashoka University · Dec 2026
Economics research examining how tax policy shapes drug use patterns. Built an econometric model in Stata using survey and policy datasets to test the relationship between changes in taxation and shifts in consumption behavior across different populations.
BSc Economics & Finance candidate at Ashoka University with a CS minor. I turn messy data into research, financial models, and civic tech, from tax policy to stock screening to solving problems.
I grew up in Addis Ababa and moved to Delhi to study Economics and Finance with a CS minor at Ashoka University. I focus on the intersection of data, policy, and technology. I've researched how tax policy affects drug use, built and backtested models to screen top Nifty 500 stocks, and I'm developing a platform that connects East African students to local solutions. I also interned as a venture analyst, evaluating early-stage startups, and led several student organizations. I'm seeking an externship to combine rigorous analysis with real-world impact.
Experience
Counselor
Ashoka's Young Scholars Programme · May 2026 - Jun 2026
Venture Analyst Intern
Birrama Venture Studio · Jun 2025 - Aug 2025
Education
Ashoka university
BSc Economics & Finance · Class of 2027
Skills
Personal Project · Jan 2026
A web platform combining Reddit-style discussion with GitHub-style solution tracking, where students across East Africa post local problems, then browse and adapt solutions that already exist elsewhere in the world.
A web platform combining Reddit-style discussion with GitHub-style solution tracking, where students across East Africa post local problems, then browse and adapt solutions that already exist elsewhere in the world.
Designing the platform so each posted problem can link to existing external solutions, tracked and iterated on in a GitHub-style structure. Building a financial breakdown for each solution so users can judge implementation cost and feasibility before adapting it locally.
Currently in development. The goal is to cut down duplicated effort across the region by connecting local problems directly to proven external solutions, with discussion and cost analysis built into a single tool.
Ashoka University · Dec 2026
Economics research examining how tax policy shapes drug use patterns. Built an econometric model in Stata using survey and policy datasets to test the relationship between changes in taxation and shifts in consumption behavior across different populations.
Economics research examining how tax policy shapes drug use patterns. Built an econometric model in Stata using survey and policy datasets to test the relationship between changes in taxation and shifts in consumption behavior across different populations.
Designed the empirical strategy from scratch: sourced and cleaned multi-source survey and policy data, merged datasets, and built regression models in Stata. Iterated on model specification to isolate the tax effect from confounding variables, then cross-checked results against existing public health and tax policy literature.
Presented the full methodology, findings, and policy implications to faculty for review. The analysis strengthened my applied econometrics skills and gave me a concrete framework for evaluating how fiscal policy shapes real-world behavior.
Ashoka University · Aug 2026
A Python-based screening tool that identifies Nifty 500 stocks likely to land in the top 20% of excess returns relative to the benchmark. Built to compare how different modeling approaches perform at predicting relative outperformance.
A Python-based screening tool that identifies Nifty 500 stocks likely to land in the top 20% of excess returns relative to the benchmark. Built to compare how different modeling approaches perform at predicting relative outperformance.
Built and trained multiple predictive models in Python on historical price and fundamental data, then backtested each out-of-sample to evaluate accuracy. Iterated on feature selection and model choice based on backtest performance, comparing trade-offs between approaches on precision and robustness.
Presented the full methodology, results, and limitations to faculty for review. The top-performing model consistently flagged stocks that outperformed the benchmark, and the project deepened my hands-on experience with applied quantitative finance and model validation.