Barinder Singh — Quant Finance Portfolio

Electrical Engineering undergrad (final year) · 22 · targeting Quant Developer and Quant Researcher roles

I build quantitative systems from the hardware up. My background in EE gives me a natural home in the low-level end of quant infrastructure — cache-line-aware C++, memory-mapped I/O, hardware timing — and I pair that with rigorous Python research and modelling work. This repository is a sequenced record of that work, built in public.

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Projects

#	Project	Role Target	Stack	Headline
2	L2 Market Data Gateway	Quant Developer	C++20, Boost.Beast, simdjson, Python	Lock-free SPSC ingestion pipeline for crypto L2 data. Queue transit p99 = 7.4 µs on live Bybit Futures. Hierarchical bitboard order book with O(1) best-price lookup via hardware intrinsics.
1	Microgrid MDP	Quant Researcher	Python, NumPy, Pandas	Markov Decision Process model for optimal energy dispatch in a microgrid. Dynamic programming solution with sensitivity analysis across demand and generation scenarios.

Projects are numbered in build order. Each has its own README, deep technical notes, and analytical instrumentation.

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What I Can Do

Systems side (QD)

• Lock-free concurrent data structures — SPSC ring buffers, atomic memory ordering, cache-line discipline
• Hardware-aware C++ — alignas(64), __rdtscp timing, mlock'd memory, thread affinity, real-time scheduling
• Market microstructure engineering — L2 order book reconstruction, sequence-gap detection and recovery, fixed-point arithmetic
• Cross-platform build systems (CMake, GCC/Clang/MSVC)

Research side (QR)

• Stochastic modelling — Markov chains, dynamic programming, MDP formulations
• Statistical analysis and backtesting in Python — pandas, NumPy, SciPy
• Data pipeline design — ingestion, normalization, storage, visualization
• Latency analysis and instrumentation — Plotly dashboards, percentile decomposition, root-cause attribution

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Background

I am a final-year Electrical Engineering student with a strong pull toward quantitative finance. EE gave me the foundation: signals, systems, linear algebra, probability, and a habit of thinking in hardware constraints rather than abstractions. I have redirected that toward financial systems — first through research-oriented modelling (Project 1), then through production-infrastructure engineering (Project 2).

The projects are intentionally sequenced to cover both sides of a quant firm's hiring surface. I understand that QR and QD are distinct roles with distinct skill demands, and the work here reflects that distinction rather than blurring it.

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Structure

quant-portfolio/
├── project-1-microgrid-mdp/          # QR: Python, MDP, dynamic programming
└── project-2-L2-market-data-gateway/ # QD: C++20, HFT, lock-free systems
    ├── include/                       # C++ headers
    ├── src/                           # C++ implementations
    ├── analysis/                      # Python latency analysis
    │   └── notebooks/latency_analysis.ipynb
    └── notes/Engineering_Notes.md     # Architectural thesis

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Contact

Barinder Singh

• GitHub: @berryO307
• Email: barindersinghdhanoa@gmail.com
• LinkedIn: www.linkedin.com/in/berry07

Open to internship and full-time opportunities in quant finance — both QR and QD tracks. Happy to walk through any part of the work in technical detail.