AI Resolutions
Head of Artificial Intelligence

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Company Description
AI Resolutions is a UK-based technology company dedicated to transforming the insurance sector with advanced artificial intelligence solutions. The team builds AI tools specifically designed for Lloyd’s of London underwriters, enabling rapid risk assessment and smarter underwriting decisions. Its products span smart underwriting, claims intelligence, risk analytics, and secure data integration, all tailored to UK insurance workflows. With capabilities in automated risk scoring, fraud detection, predictive loss modeling, and real-time data synchronization, AI Resolutions helps insurance organizations improve accuracy, efficiency, and capital allocation. The company focuses on seamless integration with existing platforms, giving clients access to modern AI without disrupting established operations.
Role Description
The Head of Artificial Intelligence is a full-time, hybrid role based in the Greater London Area. This position leads the end-to-end AI strategy, including the design, development, deployment, and ongoing optimization of machine learning solutions across underwriting, claims, risk analytics, and data integration products. Day-to-day responsibilities include overseeing research and experimentation, guiding model architecture decisions, and ensuring robust, secure, and compliant AI systems that align with insurance industry standards. The role involves collaborating closely with engineering, product, and commercial teams to translate market requirements into practical AI features, as well as mentoring and growing a multidisciplinary AI team. The Head of AI will also engage with clients and partners to explain technical approaches, influence the product roadmap, and represent AI Resolutions in industry and academic forums.
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I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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Qualifications


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- Strong foundation in Computer Science, including algorithms, data structures, distributed systems, and software engineering best practices.
- Expertise in Data Science and Pattern Recognition, including statistical modelling, supervised and unsupervised learning, and model evaluation.
- Advanced experience with Natural Language Processing (NLP), particularly in document analysis, slip processing, and text-based risk or claims intelligence.
- Practical experience with Computer Vision or related perception technologies, especially where unstructured documents or imagery support risk and claims assessment.
- Proficiency in modern ML frameworks and tooling (e.g., Python, PyTorch, TensorFlow, scikit-learn, SQL/NoSQL data stores, MLOps platforms).
- Prior leadership experience building and managing AI or ML teams, with a track record of delivering production-grade models in real-world systems.
- Background in insurance, financial services, or other regulated industries is highly beneficial; familiarity with Lloyd’s or UK insurance markets is a plus.
- Advanced degree in a relevant field (e.g., Computer Science, Data Science, Mathematics, Statistics, Machine Learning) or equivalent practical experience.
- Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders and engage in strategic discussions with senior leaders.
- Commitment to responsible AI practices.
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