Quant
Markets & crypto infrastructure
Quantitative Researcher at Vigil Markets (Nuveaux Trading): Python crypto volume analysis, counterparty risk, underwriting cost, assembly-level optimizations, and on-blockchain clearinghouse risk mapping.
4+ years · industry, research & founding
Sandra Cai
Rigorous financial analysis, shipped infrastructure, and public research: one standard of proof.
I bring four years of work experience as an operator: full-time and internship roles, institutional research, and founding work, spanning quant crypto infrastructure, blockchain finance at Microsoft Research Asia, private cloud at JD.com, independent equity and macro research, and product engineering (including Plurall AI and award-winning AI and blockchain builds).
Also a student: Computer Science at NYU with minors in Mathematics and BEMT; coursework includes ML, deep learning, NLP, security, and systems, in parallel with the work above.
Markets & quant
Research
AI & systems
SandraGPT
Ask what you want to know
Work, startups, trading comps, research, school, or say hi.
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Analysis connects markets, systems, and product, from clearinghouse risk to open-source quant work.
01
Accelerating work that ships
A cross-section of professional experience: quant pipelines, institutional research, cloud scale, and entrepreneurial engineering.
Institutional
Research & cloud
Blockchain financial research at Microsoft Research Asia; private cloud infrastructure at JD.com, from protocol questions to systems at scale.
Product
AI, blockchain & founding
Founder, Plurall AI (deepfake detection); PennApps Best Blockchain Project-winning AI and blockchain application. Code on GitHub.
02
Independent research & markets
Written on my own time: equity pitches, open-source quant work, Bayes, and AI macro. More on LinkedIn and Medium; essays on Substack.
- AVAV investment thesis. Twelve months of work on AeroVironment: fundamentals, positioning, defense-sector tailwinds. Read on Perplexity →
- Inside the Ban (Jane Street × India): open-sourced quantitative autopsy of the two-legged strategy and SEBI enforcement (July 2025); repo and thread on LinkedIn. LinkedIn post →
- Theorem of Wisdom (Bayes): white paper on Bayes' theorem for rational decision-making; open on GitHub, announced on LinkedIn. Also presented related work at NYU URC (1,000+ attendees). LinkedIn post →
- AI & macro (Medium): Oscar should be given to AI · Hawkish vs. dovish…
- Trading: ranked #1 on the Duke Fintech Trading Competition scoreboard (risk-adjusted / Sharpe-style rules). Live scoreboard → · Winner, Phoenix Trading Competition (crypto, New York Tech Week 2023).
03
Academic
NYU: Computer Science with minors in Mathematics and BEMT (Business of Entertainment, Media and Technology). Coursework includes algorithms, ML, deep learning, NLP, operating systems, software engineering, and computer security, alongside the professional track above.
Perspective
Rigor as
infrastructure
Whether it is a clearinghouse model or a stock pitch, I care about assumptions you can defend, and the engineering to test them.
04
Three things I believe
Show the work
Claims need data, mechanism, and a path to being wrong, in markets and in code.
Systems and incentives
Microstructure, risk, and infrastructure: the same clarity whether you are reading a tape or a log line.
Ship and iterate
Research informs builds; builds stress-test research. Public writing keeps both honest.
Writing · Substack · Medium · LinkedIn · Code · GitHub · sandraxcyj@gmail.com