Quant/Data/Trading Systems Lead
Költségvetés: $1000.0
FIXED /
⭐ 5.00 (5)
Singapore
data-analysis, microsoft-excel, data-science, python
Seeking a Quantitative Trading Systems Lead to develop an AI-assisted crypto trading bot. Responsibilities include designing trading strategies, integrating AI models, and optimizing performance. The role requires expertise in quantitative finance, data analysis, and trading systems. The candidate will lead a team to build a scalable and reliable trading platform.
Project:
I am building a crypto trading research and bot system with AI coding agents. The system studies wallet behavior, trading patterns, raw fills, PnL, timing, and signal candidates across BTC, ETH, SOL, and HYPE.
Football prediction system which relates to the current system we would be building. Required to use prior data and find edges in market inefficiency and on odds.
The goal is not generic indicators. The goal is wallet intelligence:
- find profitable wallet behavior
- map repeatable trade patterns
- separate real signal from noise
- avoid lookahead bias
- avoid pooled/clustering mistakes
- turn validated patterns into bot trigger logic
I need someone experienced enough to help drive this project to completion with AI tools, not just follow small tasks.
Required skills:
- Python
- pandas / CSV / JSON / SQL
- backtesting or replay logic
- trading PnL, fees, win rate, drawdown, sample size
- crypto market structure basics
- pattern recognition from time-series / event data
- bot/signal system thinking
- ability to review AI-generated code and reports critically
Strong bonus:
- quant trading experience
- Hyperliquid or crypto perp experience
- wallet/on-chain/off-chain trading data experience
- event-driven bot systems
- no-lookahead backtest design
- data pipeline debugging
Main work:
- review AI-generated research and code
- identify bad assumptions
- verify counts and results from files/data
- help design clean pattern-mining methods
- help convert valid patterns into bot signal specs
- keep system modular: each wallet/pattern stands on its own
- write clear task briefs for AI agents
- review output before anything becomes trusted
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