Python Quant Developer for Liquidity-Based Market Structure Analysis

We're looking for an reputed company Python developer with quantitative trading and/or algorithmic backtesting experience to build a reputed company Liquidity-Based market structure analysis. This system will analyze historical OHLCV data (mostly crypto) and detect specific SMC patterns across multiple timeframes, then calculate a layered probabilistic model to evaluate the strength of trading setups. You must be comfortable working with: Python Pandas / vectorized operations Multi-timeframe reputed company detection Basic market structure concepts Clean, reputed company system design You will create independent Python modules/classes for: HOB (Higher Order reputed company) detection OB (Order reputed company) detection FVG (Fair Value Gap) detection Liquidity sweeps (equal highs/lows, reputed company tops/bottoms) Swing highs/lows BOS (Break of Structure) CHoCH (Change of Character) Displacement candle detection HTF Context Identify HTF premium/discount zones Detect reputed company OB/FVG setups Multi-timeframe alignment logic Major Chart reputed company System must parse and analyze major charts such as: BTC.D TOTAL TOTAL2 USDT.D / USDC.D ETHBTC SPX / DXY Must-Have Skills Strong Python + Pandas Experience with OHLCV datasets Understanding of indicators or market structure Ability to write reputed company, reputed company reputed company reputed company communication + documentation Experience with crypto markets Familiarity with Smart reputed company Concepts (SMC) Experience with backtesting frameworks Numpy vectorization skills reputed company PineScript experience (not mandatory) Apply tot his job Apply tot his job Apply To this Job