TWG Global aims to drive innovation and business transformation across industries such as financial services, insurance, and technology by leveraging data and AI as core assets. The company seeks to deliver real-time intelligence and interactive business applications to empower informed decision-making, particularly in trading desks, portfolio optimization, and risk analytics for fixed income, derivatives, and structured products.
Requirements
- 8+ years of experience building and deploying machine learning systems in production environments, preferably in investment banking, fixed income trading, or hedge funds, ideally within enterprise or platform-scale settings.
- Proven track record of leading ML projects from ideation to production, including cross-functional collaboration and technical ownership.
- Deep expertise in supervised, unsupervised, reinforcement learning or statistical modeling.
- Experience with multimodal, generative AI, or large language models (e.g., LLMs, diffusion models) is a strong plus.
- Proficiency in Python, along with modern ML and data stack tools (e.g., TensorFlow, PyTorch, scikit-learn, JAX, Ray, MLflow).
- Hands-on experience with MLOps principles and frameworks (e.g., CI/CD pipelines for ML, model monitoring, reproducibility).
- Strong understanding of cloud-based ML infrastructure (e.g., AWS SageMaker, GCP Vertex AI, or similar).
Responsibilities
- Design and deploy ML systems that solve high-impact business problems for critical workflows.
- Develop and implement advanced ML methods including time series forecasting, reinforcement learning, optimization algorithms, and probabilistic modeling.
- Lead the adoption of emerging ML techniques and tools (e.g., generative AI, LLM fine-tuning, vector databases, RAG) through rapid prototyping.
- Partner with AI researchers and data scientists to translate experimental models into production-ready systems, supporting scaling and generalizability across business domains.
- Own the development of foundational models and platform capabilities that serve as building blocks for downstream AI applications across the organization.
- Ensure ML models are designed with safety, fairness, and transparency in mind, and aligned with internal governance frameworks and external regulatory standards.
- Design ML-driven pricing models for fixed income securities, derivatives, and structured products.
Other
- Strong foundation in fixed income analytics, derivatives pricing, and risk management.
- Commitment to responsible AI, including model fairness, transparency, and compliance with regulatory standards.
- Master’s or PhD in Computer Science, Machine Learning, Statistics, or a closely related discipline.
- Exceptional communication and collaboration skills, with the ability to translate technical details into strategic decisions.
- Hands-on experience with Palantir platforms (e.g., Foundry, AIP, Ontology) - including developing, deploying, and integrating machine learning solutions within Palantir’s data and AI ecosystem.
