Data Scientist

The Organization At TWG Group Holdings, LLC ("TWG Global"), we drive innovation and business transformation across financial services, insurance, technology, media, and sports using 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 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. By leveraging relationships with top tech startups and universities, we help create competitive advantages and drive enterprise innovation, supporting our goal of sustained growth and superior returns across our businesses. The Role As the Staff Machine Learning Engineer (VP) on the AI Science team, you will design and deploy production AI systems that power investment banking and capital markets workflows across the enterprise. Reporting to the Executive Director of AI, you will build AI‑powered products delivering measurable business outcomes for senior stakeholders. In this hands‑on individual contributor role, you will spend the majority of your time designing, building, and shipping systems while guiding the organization’s AI investments. 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 accuracy, auditability, and reliability standards. 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 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 business domains. Own the development of reusable AI capabilities and platform components that serve as building blocks for downstream applications, setting engineering standards. 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 pairing—raising technical excellence across the team. Qualifications 8+ years of experience building and deploying software or ML systems in production, with significant experience in financial services—preferably investment banking, asset management, fixed income, or credit markets. Proven track record of leading AI/ML projects from ideation to production, including cross‑functional collaboration and direct engagement with business stakeholders. Hands‑on experience building production LLM applications: prompt engineering, orchestration (e.g., multi‑agent systems, chained workflows), retrieval‑augmented generation, structured output parsing, and evaluation pipelines. Deep expertise in at least one of supervised/unsupervised learning, statistical modeling, NLP, or information extraction from unstructured documents. Strong foundation in investment banking and capital markets concepts—including valuation methodologies (DCF, comps, precedent transactions), credit analysis, fixed income analytics, and financial statement interpretation. Proficiency in Python, along with modern AI/ML tools (PyTorch, scikit‑learn, LangChain/LangGraph, vector databases, LLM APIs), with working knowledge of MLOps practices (CI/CD, model monitoring, evaluation) and cloud infrastructure (AWS, GCP, or similar). Exceptional communication and collaboration skills, with the ability to translate technical details into strategic decisions and present directly to senior financial services stakeholders. Master’s or PhD in Computer Science, Machine Learning, Statistics, Financial Engineering, or a closely related discipline preferred. Preferred Qualifications Hands‑on experience with enterprise data and AI platforms (e.g., Palantir Foundry or similar), including developing, deploying, and integrating AI solutions within an integrated data ecosystem. CFA or FRM certification. Prior experience in a client‑facing capacity within financial services. Position Location This is a hybrid position based out of our New York, NY office. Compensation The base pay for this position is $290,000‑300,000. A bonus will be provided as part of the compensation package, in addition to the full range of medical, financial, and other benefits. TWG is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. #J-18808-Ljbffr