Hi My name is Thembaletu.

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A quantitative Finance Option pricing-engine built in #Rust - Black Scholes known variables, property testing: https://github.com/KhodingNow/A-RustOption-Trading_Engine-blackScholes-

THIS IS NOW a CRATE at crates.io from last week.

🧠 RUST FOCUS SUMMARY Rust systems engineer working at the intersection of: • numerical modelling • secure systems design • financial engineering with hands-on experience in: • FFI correctness and ABI boundary safety • correctness-driven financial models • security-critical Rust systems • encoding domain invariants as executable tests My engineering philosophy is correctness-first: • Make unsafe boundaries explicit • Encode financial and mathematical invariants as tests • Use Rust’s type system to model domain constraints • Design deterministic, auditable systems suitable for financial infrastructure I am particularly interested in: • Rust ↔ C interoperability (bindgen, unsafe boundary containment) * Rust_Python bindings(pyo3, maturin) • correctness-driven quantitative engines • automatic differentiation & sensitivity frameworks • Rust for trading, pricing, and risk systems

🚀 SELECTED RUST PROJECTS

1. Advanced Rust–C FFI Debugging & Bindgen Repository: https://github.com/KhodingNow/debugging-bindgen-for-a-Rust_C-advance_FFI What This Demonstrates • Real-world FFI debugging beyond toy examples • Deep understanding of: ◦ ownership across language boundaries ◦ ABI layout and struct alignment ◦ unsafe containment strategies • Diagnosing and correcting incorrect bindgen output Key Focus Areas • Memory layout and alignment correctness • Safe abstractions over unsafe C APIs • Reasoning about memory safety under cross-language constraints

2. Rust Option Pricing Engine (Published Crate) Black-Scholes + Binomial CRR Repository: https://github.com/KhodingNow/A-RustOption-Trading_Engine-blackScholes Crate: Published on crates.io as rust-option-engine

Status • Public Rust crate (v0.1.0) published and installable via Cargo • Closed-form pricing aligned with the architecture of quantsupport (beta contribution in progress) • Binomial pricer integration being designed to align with tape-based automatic differentiation

What This Demonstrates • Translation of quantitative models into production-grade Rust code • Designing reusable financial libraries (not just standalone scripts) • Numerical validation through invariant-driven testing • Alignment with industry concerns: correctness, stability, extensibility

Highlights • Black-Scholes closed-form pricing (European options) • Cox-Ross-Rubinstein (CRR) binomial tree (backward induction) • Finite-difference Greeks (Delta) • Property-based testing using proptest • Structured for integration with AD-based sensitivity frameworks

Financial Invariants Enforced via Tests • Intrinsic value bounds • Discounted lower bounds • Put-call parity • Monotonicity with respect to volatility • Stability of finite-difference sensitivities

Engineering Positioning This project is intentionally focused on: • model correctness over trading strategy • numerical robustness over premature optimisation • architectural extensibility toward quant libraries It reflects practical quant engineering: building verifiable models that can be trusted in production systems

⚙️ ADDITIONAL RUST SIGNALS • CLI tools in Rust for security automation • Advanced error handling (Result discipline, domain-specific errors) • Cryptographic key management implementations • Public speaking on Rust for secure systems • Organizer & contributor within Rust developer communities in Johannesburg

🎓 BACKGROUND • Post-Graduate Certificate in Econometrics — Wits University → calculus, probability, statistics, stochastic modelling • Extensive experience in API security & correctness engineering • Active Rust community leadership (Microsoft Rust User Group Johannesburg) * BA Hons Psychology - University of Fort Hare (Alice, Eastern Cape)

🎯 DIFFERENTIATING PROFILE A rare combination of: • Mathematical reasoning • Systems-level Rust engineering • Security mindset • Open-source financial library contribution Positioned for roles in: • quantitative engineering • trading & pricing systems • fintech infrastructure • secure financial platforms

In April 2024, I discovered an API vulnerability on a Cloud Based API for a Retail Client's Job website - I wrote a report, informed them and they email to acknowledge it.

My Rust Engineering type-system thinking allows me to cross-pollinate the domaing type security FIRST mindset to TypeScript so that Developers who work on Cloud Platforms for example can shift security left and design APIs that invalidate unauthorised states - this does NOT eliminate their SAST vulnerabilities scanning but reduce what their SAST tools find by 80%. That is 80% less of what Security in their teams has to review!

This mindset is inspired by the Rust tools I have written and one is published...(rust-option-engine) on crates.io.

<img src=" Pictures\Screenshots\Screenshot 2024-07-04 102831.png" </>

🌍  I'm based in Johannesburg* ✉️ 

You can contact me at khodingtata@gmail.com* 🧠  I Execute DoS attacks, fingerprinting Rest and GraphQL vulnerabilities on GraphQL implementing servers, mitigate these attacks. Show HOW you can avoid them in the first place*

🤝  I'm open to collaborating on API and writing secure code projects

I embark on Front End Development, with the idea of getting into the mindset of a developer when thay make APIs, my sole interest is to build, break APIs, so I can fortify them against bad actors.

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