Quantitative Trading Analyst $$ Offline

Role overview

We’re looking for a Quantitative Strategy Analyst who’s passionate about data, trading systems, and optimization.
You’ll backtest, analyze, and fine-tune algorithmic trading strategies, helping identify top performers ready for live trading.

Required Skills & Experience

• 1–3 years of hands-on experience in quantitative analysis, algorithmic trading, or data analytics
• Strong Python skills with libraries like Pandas, NumPy, Matplotlib, and Jupyter
• Understanding of technical indicators (EMA, ATR, VWAP, RSI, MACD, etc.)
• Familiarity with backtesting best practices — avoiding lookahead bias, using walk-forward and out-of-sample testing
• Solid grasp of statistics and analytical reasoning — distributions, variance, and correlation analysis
• Detail-oriented mindset with the ability to present findings clearly and visually
• Bachelor’s degree in Finance, Economics, Math, Statistics, Computer Science, or a related field

Nice to Have

• Experience with market data APIs like Databento or Polygon
• Background in futures markets (NQ, ES, YM preferred)
• Familiarity with scikit-learn, time-series analysis, or machine learning concepts
• Practical experience with Git, SQL, or Django for analytics dashboards
• Personal trading experience or strong interest in financial markets

Responsibilities

• Run backtests on existing trading strategies across different markets and timeframes
• Measure and analyze key performance metrics — win rate, Sharpe ratio, drawdown, and more
• Tune strategy parameters using optimization methods (grid search, walk-forward testing, etc.)
• Document and visualize results in Jupyter Notebooks, including equity curves and performance summaries
• Rank and compare strategies to identify those best suited for live trading
• Work closely with quant and development teams to strengthen strategy performance and reduce overfitting
• Prepare weekly reports and insights that guide future trading decisions

Tech Stack

• Languages & Libraries: Python (Pandas, NumPy, Matplotlib)
• Data Tools: Jupyter Notebooks, Databento API
• Development: VS Code / PyCharm
• Collaboration: Git / GitHub
• Reporting: Excel / Google Sheets

Project Description

We’re building a next-generation algorithmic trading platform for futures markets (NQ, ES, YM).
The team has already developed a production-ready backtesting engine and over 20 trading strategies.
Your role will focus on analyzing, optimizing, and preparing these strategies for live trading through data-driven research and performance testing.