Quantitative Finance Consultant – Python Strategy & Validation

Position Type: Part-Time / Independent Contractor Location: Remote (US-Based) or Hybrid (Chicago, IL) Project Scope: Code review, architecture advice, and risk-management consulting Project Overview We are looking for a Quantitative Trading Consultant to provide high-level technical guidance and code-review for a private algorithmic trading project. The development team has a foundational background in Python and financial concepts but requires expert advisory sessions to refine their data pipeline and implement institutional-grade best practices. Your role will be strictly advisory—acting as a subject matter expert to review code architecture, suggest methodology improvements, and optimize data strategy. Key Advisory Areas The consultant will provide technical insights across the following pillars: Model Architecture: Advising on feature engineering, data pipelines, and translating quantitative trading signals into clean Python code. Backtesting Validation: Reviewing historical data frameworks to identify and mitigate structural risks like look-ahead bias, survivorship bias, and overfitting. Risk Management & Hedging: Providing strategic guidance on portfolio mathematics, position sizing, and risk mitigation using derivatives (options/futures). Infrastructure Review: High-level consulting on API integrations with brokerages and paper-trading simulation setups. Consultant Qualifications Strong professional or academic background in Quantitative Finance, Financial Engineering, or Computer Science. Deep proficiency in Python and standard quantitative libraries (e.g., Pandas, NumPy). Ability to break down highly complex quantitative and risk concepts into actionable development milestones. Logistics & Compliance Commitment: 2–4 hours of consulting per week, conducted via remote video sessions (with screen-sharing/code review) or in-person if located in Chicago. Compliance: All communications, contract milestones, and payments will be strictly managed through Upwork.