Responsibilities‍

• Design data taxonomy for high‑frequency trading datasets including categorization, labeling, and feature engineering
• Architect schemas and time‑series structures to support scalable ML training and backtesting
• Lead AI/ML initiatives in behavioral analysis, execution optimization, anomaly detection, and alpha discovery
• Translate objectives into phased ML roadmaps with CTO collaboration
• Mentor engineers by bridging architecture design with practical code delivery
• Oversee ML lifecycle from EDA and POC prototyping to production implementation

Requirements‍

• Financial market expertise with 6+ years in quantitative research, financial engineering, or trading analytics
• AI/ML mastery applying ML to time‑series data, predictive analytics, clustering, or reinforcement learning
• Data architecture skills in organizing multi‑terabyte trading datasets including tick data and order books
• Technical proficiency in Python, Pandas, NumPy, Scikit‑learn, PyTorch, TensorFlow, and distributed computing
• Collaborative leadership with ability to articulate architectures and direct junior teams

Nice‑to‑Haves‍

• Market familiarity across equities, FX, and crypto exchanges
• 0‑to‑1 system building in entrepreneurial or high‑growth settings

Engagement Model‍

• Consultancy phase structured as retainer‑based advisory with flexible hours
• Permanent track designed to evolve into full‑time executive leadership with equity participation
• Data access offering autonomy in steering technical roadmap