2,817 AI Intern jobs in the United Kingdom

AI Engineer - Data Science

Hybrid | London, England | Engineering

Overview

The Explore Group are partnered with one of our Tier 1 clients to secure AI Engineers with strong data science expertise who are eager to develop and deliver innovative AI solutions for large scale organisations. This role requires a combination of technical skills and business understanding, working with advanced AI technologies to create impactful data driven applications.

Responsibilities

• Partner with enterprise clients to understand requirements and design tailored AI and data science solutions
• Apply statistical modelling, machine learning, and programming expertise to solve complex problems
• Explore and implement modern AI technologies including large language models, retrieval augmented generation, and advanced automation tools
• Deliver production ready solutions that integrate into existing client environments
• Engage with stakeholders at different levels, translating technical approaches into clear business outcomes
• Stay up to date with rapidly evolving AI tools and actively incorporate them into solution design

Requirements

• Strong background in data science and machine learning with solid understanding of statistics and programming
• Exposure to MLOps and experience deploying models into production environments
• Interest and practical experience in using emerging AI technologies such as co pilots, agentic frameworks, and generative AI applications
• Proven ability to manage client expectations and deliver high quality solutions in a collaborative environment
• Excellent communication skills with the ability to present technical concepts to both technical and non technical audiences

Benefits

We offer a supportive and flexible work environment with a comprehensive benefits package including:

• 25 days of annual leave plus bank holidays
• Share options and pension scheme
• Health and dental insurance options
• Professional learning and development budget
• Cycle to work scheme and technology allowance
• Referral bonus scheme
• Opportunities to work abroad for limited periods
• Regular team socials and office perks

At TWG Group Holdings, LLC ("TWG Global"), we drive innovation and business transformation across a range of industries, including financial services, 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.

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 Executive Director on the AI Science team, you will lead the design and execution of high-impact AI and data science initiatives that directly shape TWG Global's competitive advantage. Reporting to the Managing Director of AI & Data, you will act as a senior technical leader—driving enterprise-critical projects, setting technical direction, and mentoring a small team of data scientists.
• You will partner closely with senior executives across the firm to align data science solutions with strategic priorities, ensuring adoption of advanced AI methods in a responsible and scalable way. This role requires deep technical expertise coupled with the ability to influence decision-makers and deliver measurable outcomes at the enterprise level.
• Key Responsibilities:
• Lead execution of flagship AI/ML projects that drive measurable value in financial services and adjacent sectors.
• Act as senior technical authority on advanced AI methods (generative AI, causal inference, LLM-based analytics, RAG, simulation).
• Translate complex business challenges into enterprise-level data science solutions with tangible ROI.
• Mentor and guide a small team of data scientists, fostering technical excellence, rigor, and responsible AI adoption.
• Partner with business leaders, MDs, and executive committees to ensure AI initiatives align with firm-wide priorities.
• Represent TWG Global in external technical forums and partnerships with universities, regulators, and technology leaders.
• Define standards for experimentation, reproducibility, and governance of AI solutions.
• Stay ahead of emerging trends in AI/ML, advising on adoption and firm-wide capability building.

Requirements

• 10–12+ years of experience in data science or machine learning, with proven delivery of enterprise-impact projects. Strong expertise in advanced machine learning, causal inference, deep learning, and statistical modeling.
• Demonstrated success leading end-to-end projects and influencing senior stakeholders.
• Hands-on technical depth in Python (or R), cloud-based platforms, and modern ML frameworks.
• Experience mentoring or leading small, high-performing teams.
• PhD in Data Science, Statistics, Computer Science, or a related quantitative discipline.
• Recognized as a technical thought leader through publications, external talks, or open-source contributions.

Preferred Experience:

• Experience working with Palantir platforms (Foundry, AIP, Ontology) to develop, analyze, and operationalize data-driven insights within enterprise-scale environments.
• Publications in top-tier AI/ML or data science conferences or journals (e.g., NeurIPS, ICML, KDD, AAAI, ACL, JASA). Recognized contributions to the open-source data science / ML ecosystem (e.g., libraries, frameworks, toolkits, widely adopted notebooks).
• Track record of thought leadership through invited talks, keynote presentations, or leadership roles in professional societies, conferences, or meetups.
• Experience establishing standards for reproducibility, experimentation, and responsible AI.
• Familiarity with vector databases, knowledge graphs, and LLM application frameworks for advanced analytics. Cloud or AI/ML certifications (e.g., AWS ML Specialty, Google Cloud ML Engineer, Azure AI Engineer) are a plus.

Benefits

• Work at the forefront of AI/ML innovation in life insurance, annuities, and financial services.  
• Drive AI transformation for some of the most sophisticated financial entities.  
• Be part of a high-growth AI startup scaling from 30 to 80+ employees.  
• Competitive compensation, benefits, future equity options, and leadership opportunities. 
  

This is a hybrid position based in the United Kingdom.

We offer a competitive base pay + a discretionary bonus will be provided as part of the compensation package, in addition to a full range of medical, financial, and/or 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. 

• Design, build, and train machine learning models using various algorithms and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Develop and implement AI solutions for applications such as natural language processing, computer vision, predictive analytics, and anomaly detection.
• Collaborate with data scientists and software engineers to integrate ML models into production systems.
• Perform data preprocessing, feature engineering, and model evaluation.
• Stay current with the latest research and advancements in AI and machine learning.
• Optimize ML models for performance, scalability, and efficiency.
• Develop and maintain robust data pipelines for ML model training and deployment.
• Conduct experiments to test hypotheses and validate model performance.
• Communicate complex technical concepts and findings to both technical and non-technical stakeholders.
• Contribute to the development of AI strategies and best practices within the organization.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Data Science, or a related quantitative field.
• Minimum of 3-5 years of hands-on experience in developing and deploying machine learning models.
• Proficiency in programming languages such as Python, R, or Java.
• Strong knowledge of ML libraries and frameworks (e.g., TensorFlow, PyTorch, Keras, scikit-learn).
• Experience with data manipulation and analysis tools (e.g., Pandas, NumPy).
• Understanding of statistical modelling, probability, and algorithms.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and MLOps practices is a plus.
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration abilities.

• Design, build, and train machine learning models and algorithms to solve complex business problems.
• Develop and implement scalable AI solutions using Python, TensorFlow, PyTorch, and other relevant libraries.
• Process, clean, and transform large datasets for ML model training and evaluation.
• Evaluate model performance, identify areas for improvement, and iterate on solutions.
• Deploy machine learning models into production environments, ensuring robustness and scalability.
• Collaborate with data scientists, software engineers, and domain experts to define project requirements and deliver solutions.
• Stay abreast of the latest advancements in AI, machine learning, and deep learning research.
• Develop and maintain robust data pipelines and feature engineering processes.
• Contribute to the overall AI strategy and roadmap of the organization.
• Communicate complex technical findings to both technical and non-technical audiences.

• MSc or Ph.D. in Computer Science, Artificial Intelligence, Data Science, Statistics, or a related quantitative field.
• Proven experience in developing and deploying machine learning models in a professional setting.
• Strong proficiency in Python and common ML/DL frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Solid understanding of various machine learning algorithms (e.g., regression, classification, clustering, deep neural networks).
• Experience with data manipulation and analysis tools (e.g., Pandas, NumPy).
• Familiarity with cloud platforms (AWS, Azure, GCP) and their ML services is a plus.
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration abilities.
• Ability to work effectively in a dynamic and fast-paced team environment.
• Experience with Big Data technologies (e.g., Spark) is advantageous.