Senior Quantitative Researcher / Systematic Trading Expert — Institutional-Grade Optimization & Validation (MT5 + Python) — $10,000 Fixed
2 days ago
Paris
Overview We are seeking a highly experienced quantitative researcher / systematic trading specialist to lead a full institutional-grade optimization and validation process for a proprietary algorithmic trading system (“DISTARION”). This is not a retail optimization task. The objective is to elevate an already profitable, research-driven strategy into a fully validated, institutional-grade system, compliant with the standards expected by allocators, hedge funds, and systematic CTAs. The selected candidate will operate in a controlled infrastructure environment and will be responsible for executing a complete quantitative validation pipeline, from MT5 optimization to advanced statistical validation using Python and other relevant professional research tools. Context & Existing System • Proprietary algorithmic trading system already developed and operational (MQL5), • Instruments:, • Primary: NASDAQ futures proxy (US100.pro → CME E-mini Nasdaq-100 Futures (NQ)), • Secondary: USDJPY (cross-asset hedging component), • Data:, • Institutional-grade datasets sourced via professional CME-linked providers, • Historical coverage: 2011–2026, • Sampling: 1-minute data, strategy operating on M15 timeframe, • The strategy was designed through research prior to coding, not curve-fitted post-hoc Project Objective The goal is to produce: A fully validated, statistically robust, institution-ready systematic trading system, supported by: • rigorous optimization, • overfitting control, • statistical validation, • professional reporting, • future capital allocation at scale, • external audit / due diligence, • institutional presentation Additional Documentation & Research Framework In addition to this job description, the selected candidate will receive: • A detailed PDF document explicitly outlining the full quantitative optimization requirements, which goes significantly beyond the summarized Scope of Work below, • This document will include:, • detailed optimization expectations, • extended validation requirements, • advanced methodological guidelines “The DISTARION Optimization Roadmap: From MT5 Backtest to Institutional-Grade Validation” Based on this: • Candidates must indicate whether they already have access to and experience with the relevant tools/platforms described, • If not, they must clearly specify:, • which tools, platforms, or research environments they intend to use Infrastructure & Working Environment The work will be conducted under a controlled architecture: • Algorithm Access, • Provided as compiled EX5 file, • Protected via temporary license system (time-bound + environment-bound), • Execution Environment, • Work performed on a private VPS fully controlled by the project owner, • Hybrid compute setup:, • VPS (primary environment), • Local high-performance machine (i9 / 24 cores) connected as compute node, • Optional scaling via MQL5 Cloud Network, • Security, • Additional private contractual agreement, • Strict limitations on code access, reverse engineering, and data extraction Scope of Work (Full Quant Pipeline) The selected candidate will be responsible for executing a complete institutional optimization and validation pipeline, including but not limited to: 1. Advanced MT5 Optimization Framework • Design and execute:, • Genetic optimization (broad exploration), • Exhaustive optimization (local refinement), • Implement custom optimization criteria (OnTester):, • multi-factor scoring (Sharpe, drawdown, recovery factor, trade count), • Enforce:, • minimum trade thresholds, • drawdown constraints, • parameter discipline (avoid over-parameterization), • Perform:, • parameter surface analysis (2D/3D), • identification of robust plateaus vs overfit spikes 2. Overfitting Control & Robustness Engineering • Parameter stability testing (±10–20%), • Sensitivity analysis, • Perturbation testing, • Slippage and execution stress tests, • Commission stress testing 3. Walk-Forward Analysis (Institutional Standard) • Rolling walk-forward optimization (NOT single split), • Configurable IS / OOS windows, • Walk-Forward Efficiency (WFE) computation, • Walk-Forward Matrix testing 4. Monte Carlo Simulation • Trade reshuffling, • Bootstrapping (10,000+ iterations), • Extraction of:, • 95% worst-case drawdown, • Sharpe distribution, • probability of ruin 5. Statistical Validation • Deflated Sharpe Ratio (DSR), • t-statistics (with multiple testing corrections), • Sharpe confidence intervals (Lo adjustment), • Probability of Backtest Overfitting 6. Python-Based Analysis Pipeline As outlined in the roadmap : • Export MT5 results (XML / frames / CSV), • Build Python pipeline:, • pandas / numpy, • QuantStats (full tear sheets), • Monte Carlo extensions, • Generate:, • institutional-grade performance reports, • equity curve diagnostics, • regime analysis 7. Regime & Cross-Asset Analysis • Segment performance by volatility regimes, • Evaluate robustness across market conditions, • Validate partial transferability across correlated assets 8. Cross-Asset Portfolio Construction The system must be extended to a portfolio framework: • NQ + USDJPY combined, • Example allocation:, • 0.5% risk NQ, • 0.5% risk USDJPY, • vs 1% standalone per asset, • Ensure:, • simultaneous execution compatibility, • improved risk-adjusted performance, • reduced drawdown via diversification 9. Multi-Asset Optimization Deliverables Deliverables required in two phases: Phase A — NQ (Primary Focus) • Full optimization + validation, • Institutional metrics improvement:, • Sharpe ratio, • max drawdown, • recovery factor, • Joint optimization, • allocation logic, • portfolio-level metrics 10. Final Deliverables The candidate must provide: • Optimized .set files (multiple variants if relevant), • Full optimization reports, • Walk-forward reports, • Monte Carlo analysis, • Statistical validation outputs, • Python scripts (clean & reusable), • Institutional-grade performance tear sheets, • Documentation of methodology Performance Expectations The objective is NOT to maximize returns blindly. The priority order is: • Sharpe Ratio (risk-adjusted performance), • Drawdown control Candidate Requirements We are only interested in top-tier profiles. You must demonstrate: • Proven experience in:, • systematic trading, • quantitative research, • MT5 optimization OR similar platforms, • Strong Python quant stack:, • pandas / numpy / statistical analysis, • Deep understanding of:, • overfitting, • walk-forward analysis, • Monte Carlo, • statistical validation, • Prior work on:, • hedge fund strategies, • CTA / systematic portfolios, • institutional research pipelines Selection Process • Highly selective, • Candidates must:, • provide track record and relevant experience, • clearly explain their methodology and validation approach, • A video call will be organized prior to contract award in order to:, • assess technical depth, • validate understanding of institutional standards, • align on execution approach Timeline • There is no strict hard deadline An ideal target timeline would be end of July 2026 Candidates are expected to: • confirm whether this timeline is realistic, • provide an estimated execution schedule Compensation • Fixed: $10,000, • Potential for long-term collaboration if performance meets expectations Final Note This project is being developed with the objective of future capital deployment at scale. As such: The work must meet institutional standards in terms of rigor, reproducibility, and robustness. No shortcuts, no superficial optimization.