VP, Data Science / Machine Learning Lead - Capital Markets & Fixed Income

The Organization

At TWG Group Holdings, LLC (“TWG Global”), we drive innovation and business transformation across a range of industries, including financial services (particularly capital markets and fixed income), insurance, technology, media, and sports, by leveraging data and AI as core assets. Our AI-first, cloud-native approach delivers real-time intelligence and interactive business applications, empowering informed decision-making for both customers and employees.

We prioritize responsible data and AI practices, ensuring ethical standards and regulatory compliance. Our decentralized structure enables each business unit to operate autonomously, supported by a central AI Solutions Group, while strategic partnerships with leading data and AI vendors fuel game-changing efforts in marketing, operations, and product development. Our solutions power trading desks, portfolio optimization, and risk analytics across fixed income, derivatives, and structured products.

You will collaborate with management to advance our data and analytics transformation, enhance productivity, and enable agile, data-driven decisions. By leveraging relationships with top tech startups and universities, you will help create competitive advantages and drive enterprise innovation.

At TWG Global, your contributions will support our goal of sustained growth and superior returns, as we deliver rare value and impact across our businesses.

The Role

As the Staff Machine Learning Engineer (VP) on the AI Science team, you will be responsible for designing and deploying production AI systems that power investment banking and capital markets workflows across the enterprise. Reporting to the Executive Director of AI, you will play a critical role in building AI-powered products that deliver measurable business outcomes for senior stakeholders including Managing Directors and portfolio managers.

You will bridge AI engineering and capital markets, combining deep understanding of investment banking valuation, fixed income markets, and credit analysis with hands-on ability to build and ship LLM-powered products at speed. You will have direct visibility to senior business stakeholders, translating complex business workflows into working AI systems.

This is a hands-on individual contributor role: you will spend the majority of your time designing, building, and shipping systems, while acting as a technical thought leader who helps shape the direction of the organization’s AI investments and fosters a culture of rapid iteration, rigorous evaluation, and responsible AI.

Key Responsibilities:

Design and deploy AI systems that automate high-impact investment banking and capital markets workflows—compressing multi-hour analytical tasks into minutes while meeting the accuracy, auditability, and reliability standards of front-office users.

Build and own production LLM pipelines end-to-end: structured extraction from complex financial documents, retrieval-augmented generation, multi-step orchestration, and structured output parsing.

Evaluate and champion emerging AI techniques and tools (e.g., agentic workflows, LLM evaluation frameworks, vector databases, RAG architectures) through hands-on prototyping, benchmarking, and iterative deployment.

Partner with AI researchers, data scientists, and domain experts to translate experimental models into production-ready systems—hardening prototypes for latency, cost, accuracy, and reliability while generalizing solutions across multiple business domains.

Own the development of reusable AI capabilities and platform components that serve as building blocks for downstream applications across the organization, setting the engineering standards for how AI systems are built, evaluated, and maintained.

Collaborate directly with senior business stakeholders (Managing Directors, portfolio managers, research analysts) to understand workflows, gather feedback, and iterate on AI products that meet practitioner-grade quality standards.

Build AI-driven analytics for fixed income and credit markets that fuse quantitative signals with unstructured data—turning market data, filings, and research into decision-ready insight for investment professionals.

Mentor engineers and data scientists through design reviews, code reviews, and hands-on pairing—raising the bar for technical excellence and engineering rigor across the team.