Quant Research Analyst – Pattern Discovery & Signal Correlation (AI-Driven Trading)
# Description: We are a stealth FinTech startup using proprietary data mining and machine-learning models to predict short-term market volatility and price movement. Our system produces probability scores and trade picks, and we are actively testing automated trading strategies. We’re looking for a quant-oriented finance analyst to analyze our model outputs and identify additional technical, statistical, or market patterns that correlate—or anti-correlate—with gains and losses leading into purchase points. This role is focused on signal discovery, validation, and interaction analysis, not discretionary trading. You must be quant-focused, be fluent in english and be able to read/write/speak coherently. # What you’ll do: - analyze our probability scores and historical picks vs. realized outcomes - identify technical indicators or derived signals that: - strengthen winning setups - warn of false positives - negatively correlate with returns - test combinations and interactions between our ML scores and classic quant indicators - evaluate indicators commonly used on TradingView (or equivalents), including: • momentum (RSI, stochastic, MACD variants) • trend (SMA/EMA structures, regime filters) • volatility (bollinger bands, ATR, squeezes) • volume & flow (OBV, volume profile, custom flow metrics) - assess whether community or advanced indicators (e.g. squeeze momentum, wave-based or regime indicators) add predictive value - produce clear, evidence-based conclusions (what helps, what hurts, what’s redundant) # What we’re looking for: - strong quantitative background in trading, market microstructure, or signal research - experience analyzing technical indicators beyond surface-level usage - comfort with python (pandas, numpy, scipy) and statistical validation - ability to reason in probabilities, distributions, and conditional outcomes - disciplined approach to avoiding overfitting and false correlations # Nice to have: - experience with short-term or swing-based strategies - familiarity with TradingView / Quant indicators (conceptually or hands-on) - background in systematic trading, factor research, or alpha discovery - experience working alongside ML-driven prediction systems Apply tot his job