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CN2.DEVBUKYA NARESH

SECTION / 08 — WORK WITH ME

OPEN TO SELECTED WORK · RESEARCH · COLLABORATION


Research-grade engineering for quantitative problems. This is an individual practice — one person, named on every deliverable, no agency and no bench behind the curtain.

CN2.DEV / BUKYA NARESH / CN2

SCOPE ALIGNMENT

THE PROBLEM, THE BUILD, THE DELIVERABLE

I scope engagements by deliverable rather than by hours. Each row below maps a common client problem to the system that addresses it and the artifact you receive at handover.

YOU HAVE

Market question without a harness

WHAT I BUILD

Deterministic research engine + reproducible artifacts

WHAT YOU GET

A result that regenerates byte-identically, plus its limitations

YOU HAVE

Vendor and internal data that disagrees with itself

WHAT I BUILD

Point-in-time safe ingestion, validation and replay

WHAT YOU GET

One canonical model, with the failure modes quarantined and visible

YOU HAVE

A strategy that looks good and cannot be trusted

WHAT I BUILD

Adversarial tests, cost modelling and structural risk gates

WHAT YOU GET

An honest read on what the strategy actually does

YOU HAVE

Cost or financial data at volume

WHAT I BUILD

High-throughput, low-dependency processing

WHAT YOU GET

A published benchmark with its methodology attached

ENGAGEMENT AREAS

These are the areas where I can take work end to end — each one backed by systems I have already built and used in practice.

01

QUANT RESEARCH

Falsifiable market hypotheses tested with deterministic experiments and published limitations.

02

DATA INFRASTRUCTURE

Market-data and financial-data pipelines engineered for exactness, throughput and auditability.

03

TRADING SYSTEMS

Multi-timeframe systematic architectures with structural risk controls end to end.

04

BACKTESTING

Deterministic simulation harnesses with explicit cost modelling and reproducible artifacts.

05

RESEARCH AUTOMATION

Governance workflows that turn exploratory research into verifiable, promotable evidence.

06

PERFORMANCE ENGINEERING

Low-latency, high-throughput systems work where measurement context ships with the number.

CURRENTLY OPEN TO

OPEN TO · AVAILABLE FOR · INTERESTED IN

These are the shapes of work I am actively open to right now — roles, contracts and collaborations where quantitative thinking and solid engineering matter.

OPEN TO

  • Quantitative development roles
  • Quantitative research roles
  • Market-data engineering
  • FinTech / research engineering

AVAILABLE FOR

  • Technical freelance and contract work
  • Quant / FinTech engineering projects
  • Research tooling and prototyping

INTERESTED IN

  • Research collaboration
  • Open-source data infrastructure
  • Technical partnerships

STARTING POINT

01

DESCRIBE THE QUESTION

What are you trying to find out, and what would count as an answer? If that second half is unclear, that is the first thing we work on.

02

DESCRIBE THE DATA

What exists, where it lives, and what state it is in. Data reality usually determines the shape of the project.

03

AGREE THE EVIDENCE

We decide in advance what artifact would prove the work succeeded. This is fixed before anything is built.

04

BUILD AND HAND OVER

You get the system, the reproducible artifact, the published benchmark or test result, and the written limitations.

NO FORMS. NO FUNNELS. DIRECT.

START A
CONVERSATION

Describe the problem, the data, and what would count as success — that is enough to start a conversation.

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