At a Glance
- Tasks: Develop and deploy cutting-edge AI solutions across diverse industries.
- Company: Join TWG Global, a leader in innovation and data-driven transformation.
- Benefits: Competitive pay, flexible hours, and opportunities for professional growth.
- Other info: Dynamic team environment with exposure to exciting projects and career advancement.
- Why this job: Make a real impact with advanced AI technologies while collaborating with top experts.
- Qualifications: Pursuing a master's in Computer Science or related field with AI/ML experience.
The predicted salary is between 80100 - 97900 £ per year.
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.
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. Tensor Flow, Py Torch, scikit-learn, Pandas, Num Py).
- 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.
Compensation
The expected hourly rate for this role is ~$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.
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AI Data Science Intern (UK) employer: TWG Global AI
At TWG Global, we pride ourselves on being an exceptional employer that fosters a culture of innovation and collaboration. Our hybrid work model in the UK allows for flexibility while providing competitive compensation and comprehensive benefits, including future equity options. We are committed to employee growth, offering mentorship opportunities and the chance to lead high-impact data science initiatives that drive meaningful change across industries.
StudySmarter Expert Advice🤫
We think this is how you could land AI Data Science Intern (UK)
✨Join Data-Science Meetups
Get yourself along to local data-science meetups or workshops. They're goldmines for networking, and you'll learn from industry pros who might just point you in the direction of internships. Plus, discussing the latest trends with like-minded individuals can really amp up your game.
✨Utilise University Career Services
Check in with your uni's career services since they often have connections with companies looking for interns. They might even organise information sessions with firms, which can be a great chance for you to learn more about potential internships and make some key contacts.
✨Show Off Your Stuff on GitHub
If you're into data science, having a GitHub profile with your projects is essential. Make sure your portfolio is public and showcases your best work! Recruiters love to see your coding skills and problem-solving approach, and it’s a brilliant way to stand out.
✨Apply Directly on Our Website
Don’t forget to check out the internships listed on our site! It's always a good idea to apply directly through our website because it makes your application easier for our team to find, and you might just catch the hiring manager’s eye by showcasing exactly what you're passionate about in data science.
We think you need these skills to ace AI Data Science Intern (UK)
Some tips for your application 🫡
Show Off Your Technical Skills:For a data science internship, we want to see those analytical skills shine! List your programming languages, like Python or R, and make sure to highlight any relevant projects or courses you've completed. If you've dabbled with tools like Pandas, NumPy, or machine learning algorithms, don’t hold back – include those in your CV!
Share Your Curiosity in Your Cover Letter:As an intern, your motivation and eagerness to learn are key! In your cover letter, talk about specific data science concepts that excite you and how this internship at TWG Global AI will help you grow. Share what you hope to achieve and how you plan to tackle real-world data problems - we love enthusiasm!
Include Any Relevant Certifications:If you've earned any certifications, such as from Coursera or DataCamp, make sure to include these in your application. They show us that you're proactive and committed to expanding your data science skillset. This could make a real difference in how we assess your application!
Keep It Relevant and Concise:Remember, as an intern, you don’t need to have decades of experience. Focus on showcasing relevant coursework, personal projects, or even related volunteer work in data science. Keep your CV and cover letter concise but impactful – we appreciate clear and straightforward communication!
How to prepare for a job interview at TWG Global AI
✨Brush Up on Your Coding Skills
As a data science intern, you might get grilled on your programming skills. Expect to tackle some coding challenges using languages like Python or R. We recommend practising basic algorithms or data manipulation tasks so you can show off your tech skills with confidence.
✨Show Off Your Projects
Prepare to discuss any projects you’ve done, whether in your studies or on your own time. Having a strong portfolio of data analyses or machine learning models will really set you apart. We can use platforms like GitHub to showcase your work to impress TWG Global AI.
✨Know Your Stats and ML Basics
Brush up on your statistics and machine learning concepts because interviewers love to dig into this! Be ready to explain your understanding of algorithms or how you would approach a given data problem. This will highlight your theoretical background alongside your practical skills.
✨Be Eager to Learn and Adapt
Internships are all about potential and growth. Make sure you convey your eagerness to learn and adapt to new tools or methodologies. Show TWG Global AI that you’re not just looking for experience, but that you're keen to contribute and grow within the team.