Develop and productionize machine learning models and AI agents for financial-market intelligence and client workflows. Responsibilities include forecasting, sentiment analysis, market classification, LLM/RAG agent development, backtesting, hallucination testing, governance, human-review controls, provider benchmarking, regulatory compliance, and cross-functional collaboration. The role also provides technical leadership and mentorship while applying advances in AI and machine learning to financial markets.
In this role, you will play a pivotal part in developing and productionizing our proprietary ML models and AI agents, shaping the future of financial markets. Your expertise will be instrumental in enhancing our market intelligence and client workflows, ensuring we stay at the forefront of the industry.
Responsibilities- Develop ML models for various financial market regimes, forecasting, event risk assessment, sentiment analysis, and market classification.
- Construct LLM/RAG/tool-calling agents to enhance market intelligence and streamline client workflows.
- Oversee model evaluation, backtesting, hallucination testing, and release gates, ensuring the highest standards of accuracy and governance.
- Integrate quant signals, trusted data sources, and human-review controls for robust and reliable model performance.
- Benchmark model providers and explore open-source alternatives to stay ahead of the curve.
- Collaborate with cross-functional teams to align ML models and AI agents with business objectives and client needs.
- Provide technical leadership and mentorship to junior team members, fostering a culture of continuous learning and improvement.
- Stay updated with the latest advancements in AI/ML technologies and apply them to enhance our market intelligence capabilities.
- Ensure compliance with regulatory requirements and industry best practices in the development and deployment of ML models and AI agents.
- Strong proficiency in Python, with a solid understanding of ML fundamentals, including classification, clustering, time series analysis, and regime detection.
- Hands-on experience with LLM/RAG/agent technologies, demonstrating a track record of shipping models beyond notebooks.
- In-depth knowledge of financial markets, including macro, FX, rates, central banks, and economic data, with a keen understanding of market dynamics.
- Excellent judgment and decision-making skills, particularly in assessing model accuracy, governance, and the need for human-in-the-loop review.
- Experience in forecasting and nowcasting techniques is highly advantageous, as is expertise in financial NLP and fine-tuning.
- A background in quant finance or systematic strategies is desirable, providing a unique perspective on financial market modeling.
- Excellent communication and collaboration skills, with the ability to work effectively in a cross-functional team environment.
- A proactive and innovative mindset, constantly seeking opportunities to enhance our ML models and AI agents.
- A strong work ethic, attention to detail, and a commitment to delivering high-quality results.
Cantor Fitzgerald London, England Office
London, United Kingdom, 0
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