Executive Director, AI Data Scientist (Fixed Income & Investment Banking)

Key Responsibilities

• Lead flagship AI/ML projects that drive measurable value across fixed income trading, credit, rates, and investment banking workflows, from pricing and execution to risk and origination
• Direct the development of models for valuing illiquid instruments, forecasting price and spread movements, modeling prepayment and default risk, and analyzing the yield curve and interest rate dynamics
• Act as senior technical authority on advanced AI methods (generative AI, causal inference, LLM-based analytics, RAG, simulation) and on their application to quantitative finance
• Translate complex desk-level and banking challenges into enterprise-grade data science solutions with tangible P&L and risk-adjusted ROI
• Mentor and guide a small team of data scientists, building technical excellence, modeling rigor, and responsible AI adoption
• Partner with trading desks, banking coverage teams, risk, MDs, and executive committees to ensure AI initiatives align with firm-wide priorities
• Represent TWG Global in external technical forums and partnerships with universities, regulators, and technology leaders
• Define standards for experimentation, reproducibility, and model governance, consistent with the controls expected in a regulated capital markets environment
• Stay ahead of emerging trends in AI/ML and quantitative finance, advising on adoption and firm-wide capability building

Requirements

• 10 or more years of experience in data science or machine learning, with proven delivery of enterprise-impact projects, including direct work in fixed income, capital markets, or quantitative finance
• Strong expertise in advanced machine learning, causal inference, deep learning, statistical modeling, and time series analysis
• Working knowledge of fixed income fundamentals: duration, convexity, yield curves, credit spreads, rate models, and the pricing of debt instruments and derivatives
• Demonstrated success leading end-to-end projects and influencing senior stakeholders on a trading floor or within a banking or risk function
• Hands-on technical depth in Python (or R), cloud-based platforms, and modern ML frameworks
• Experience mentoring or leading small, high-performing teams
• Master's or PhD in Data Science, Statistics, Computer Science, Financial Engineering, Quantitative Finance, or a related discipline

Preferred Qualifications

• Experience working with Palantir platforms (Foundry, AIP, Ontology) to develop, analyze, and operationalize data-driven insights within enterprise-scale environments
• Familiarity with model risk management and validation standards (e.g., SR 11-7) and establishing standards for reproducibility, experimentation, and responsible AI in a regulated setting
• Experience with market and tick data infrastructure, including KDB+/q or similar time series stores
• Familiarity with vector databases, knowledge graphs, and LLM application frameworks for advanced analytics
• Cloud or AI/ML certifications (e.g., AWS ML Specialty, Google Cloud ML Engineer, Azure AI Engineer)