Coding Tutors : 1-1 Coding Lessons

Hi, I’m Ojas Srivastava, a Mathematics and Computer Science student at McGill University, where I’m diving into advanced topics like Algorithms and Data Structures (in Java), Real Analysis proofs, Compiler Design, and Operating Systems on C/Linux—challenges that sharpen my problem-solving daily. I achieved A*s in Maths, Further Maths, and Physics at A-Level (Cambridge), alongside stellar IGCSE results across sciences and maths, which ignited my passion for breaking down complex concepts into clear, relatable steps. With four years of part-time A-Level tutoring in these subjects, I’ve helped dozens of students boost grades from C’s to A’s by tailoring sessions to their style—whether visual diagrams for vectors or step-by-step proofs for calculus—plus I volunteered regularly at a local orphanage, teaching basic maths and physics to kids, building patience and adaptability for diverse learners. This mirrors my tech wins: McHacks victory with SymLang (AI gesture-coding tool, 90% accuracy via TensorFlow.js), UoFT Hacks win with CodeView (OCR code scanner with Big O analysis), and co-founding Nuclear AI notetaking app (100 users, 40% monthly growth). Internships at Nakisa (40% query speed-ups for Fortune 500) and CodeDay (leading global hackathons) honed my collaborative edge.

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Passionate professional with mathematical finance and everything utilising mathematics. I hold a CQF with Distinction, an MSc in Economics from LSE, and currently work in applied financial engineering advisory, where I benchmark and validate exotic derivatives pricing models daily — from Bermudan options and callable bonds to inflation-linked swaps and Monte Carlo simulations.
My work sits at the intersection of quantitative theory and real-world application: building independent pricing models, calibrating volatility surfaces, computing CVA/DVA adjustments, and stress-testing credit risk frameworks. I also code actively in Python, C++, and VBA, and pursue personal research in stochastic expansion methods for exotic option pricing.
In my courses, I bring this practitioner perspective directly into the classroom. If you want to understand not just the textbook formulas but how derivatives are actually priced, validated and risk-managed in industry, you’re in the right place.

Hi, I’m Ojas Srivastava, a Mathematics and Computer Science student at McGill University, where I’m diving into advanced topics like Algorithms and Data Structures (in Java), Real Analysis proofs, Compiler Design, and Operating Systems on C/Linux—challenges that sharpen my problem-solving daily. I achieved A*s in Maths, Further Maths, and Physics at A-Level (Cambridge), alongside stellar IGCSE results across sciences and maths, which ignited my passion for breaking down complex concepts into clear, relatable steps. With four years of part-time A-Level tutoring in these subjects, I’ve helped dozens of students boost grades from C’s to A’s by tailoring sessions to their style—whether visual diagrams for vectors or step-by-step proofs for calculus—plus I volunteered regularly at a local orphanage, teaching basic maths and physics to kids, building patience and adaptability for diverse learners. This mirrors my tech wins: McHacks victory with SymLang (AI gesture-coding tool, 90% accuracy via TensorFlow.js), UoFT Hacks win with CodeView (OCR code scanner with Big O analysis), and co-founding Nuclear AI notetaking app (100 users, 40% monthly growth). Internships at Nakisa (40% query speed-ups for Fortune 500) and CodeDay (leading global hackathons) honed my collaborative edge.

tbd…………………………………………………………………………………………..tbd…………………………………………………………………………………………..tbd…………………………………………………………………………………………..tbd…………………………………………………………………………………………..tbd…………………………………………………………………………………………..tbd…………………………………………………………………………………………..tbd…………………………………………………………………………………………..tbd…………………………………………………………………………………………..tbd…………………………………………………………………………………………..tbd…………………………………………………………………………………………..

Passionate professional with mathematical finance and everything utilising mathematics. I hold a CQF with Distinction, an MSc in Economics from LSE, and currently work in applied financial engineering advisory, where I benchmark and validate exotic derivatives pricing models daily — from Bermudan options and callable bonds to inflation-linked swaps and Monte Carlo simulations.
My work sits at the intersection of quantitative theory and real-world application: building independent pricing models, calibrating volatility surfaces, computing CVA/DVA adjustments, and stress-testing credit risk frameworks. I also code actively in Python, C++, and VBA, and pursue personal research in stochastic expansion methods for exotic option pricing.
In my courses, I bring this practitioner perspective directly into the classroom. If you want to understand not just the textbook formulas but how derivatives are actually priced, validated and risk-managed in industry, you’re in the right place.