About this role

The Organization At TWG Group Holdings, LLC (“TWG Global”), we drive innovation and business transformation across a diverse portfolio—including investments, finance, insurance, and media—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 the central AI Solutions Group, while strategic partnerships with leading data and AI vendors fuel transformative projects in marketing, operations, and product development. 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 industry innovation.

At TWG Global, your contributions will support our goal of sustained growth and superior returns, as we deliver significant value and impact across our businesses. The Role As a Data Science Intern with the AI/ML Center of Excellence on the United Kingdom team , you will contribute to the development and deployment of advanced AI solutions across a live portfolio of use cases spanning insurance, financial services, real-estate finance, motorsports, professional sports, prediction markets, and enterprise security.

Our work is deployment-heavy — models and agents ship into production, get used by business end-users, and are measured against business KPIs. Under the guidance of experienced team members, you will participate in projects spanning deep learning, large language models and agentic systems, document AI, time series forecasting, reinforcement learning, mathematical optimization, speech and conversational AI, and Graph AI.

You will also have the opportunity to contribute to cross-cutting product platforms in document intelligence, threat detection, and AI governance. You will work within a team committed to upholding the highest standards of trust, transparency, safety, and security in AI, ensuring ethical practices and compliance with relevant regulations. Collaboration with cross-functional teams and stakeholders — engineering, product, business leadership, and client counterparts — will be a key part of your experience, providing exposure to both technical and business aspects of AI/ML initiatives.

Key Responsibilities: Assist in the development, testing, and productionization of AI/ML models, including large language models and agentic systems, retrieval-augmented generation, document AI and structured extraction, embeddings and semantic search, tree-based and classical machine learning, time series forecasting, and mathematical optimization. Support agentic and LLM-based pipelines end-to-end: retrieval, extraction, grounding, evaluation against subject-matter-expert ground truth, and cost/latency profiling across multi-model ensembles.

Develop robust, well-structured, and testable code that meets the bar for deployment into production on cloud-native data and AI platforms, working closely with the Engineering team on integration, monitoring, and iteration once live. Participate in maintaining documentation and inventory of AI/ML projects, ensuring adherence to governance and quality standards. Collaborate with team members and business stakeholders to understand requirements and translate them into technical tasks with clear acceptance criteria.

Stay informed about emerging AI technologies and best practices, sharing insights with the team. Contribute to the measurement and reporting of project performance metrics — model accuracy, subject-matter-expert agreement rates, latency and cost, and business KPIs — both pre-launch and once in production. Requirements Qualifications: Currently enrolled in a master's program in Computer Science, Engineering, Data Science, or a related field.

Coursework or project experience in AI/ML, including exposure to at least one of the following: machine learning and deep learning, time series forecasting, reinforcement learning, optimization, or conversational AI. Familiarity with Python and common AI/ML frameworks (e.g. TensorFlow, PyTorch, scikit-learn, Pandas, NumPy). Software engineering fundamentals — version control, code review, modular design, and writing testable code intended for someone else to run in production.

Strong analytical and problem-solving skills. Ability to design machine learning experiments and define model performance metrics that ensure AI outputs are aligned with business goals. Ability to work collaboratively in a team environment. Preferred Qualifications: Hands-on experience taking a model or AI application from prototype into a deployed environment — even at coursework or hackathon scale (containerization, CI/CD, monitoring, or serving via an API).

Experience with cloud-based AI/ML and data platforms (e.g. Palantir Foundry, Snowflake, Databricks, AWS/Azure/GCP). Experience with LLM application patterns: retrieval-augmented generation, tool-using agents, multi-agent orchestration, prompt/pipeline evaluation, and grounding against subject-matter-expert ground truth. Exposure to MLOps and evaluation tooling — experiment tracking, offline/online evaluation harnesses, guardrails, and observability for LLM or ML systems in production.

Exposure to AI/ML governance, ethics, or responsible AI practices — including data-use registries, model cards, and audit trails. Benefits Compensation The expected hourly rate for this role is ~USD 36.94 GBP/hour. Position Location United Kingdom, London area preferred. TWG is an equal opportunity employer. All applicants will be considered for employment without attention to age, race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

*This job posting is not to be reposted without the explicit permission of TWG AI.

Source listing: workable_twgai