Staff Data Scientist at marshmallow

✨ The Stack take on this marshmallow job

• 🏢 marshmallow has 6 jobs here, 6 with visa sponsorship see all
• 📊 28 Data Scientist jobs in the United Kingdom in the last 60 days see them
• 🛂 Skilled Worker visa. Standard minimum salary: £41,700 a year guide
• 💡 No salary shown. Ask marshmallow if it is above the minimum.

Updated 2026-11-05, from our data and official sources.

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About the role

Responsibilities:
- Lead technical design and delivery of ML and Generative AI systems for Claims and Fraud, from prototypes to production.
- Shape system-level architecture: how models, data pipelines and workflows fit to scale decisioning and reduce time-to-production.
- Drive platform and tooling improvements (monitoring, feedback loops, QA) that enable reliable AI-driven claims automation.
- Collaborate with Product and Engineering to align technical choices with commercial goals and multi-year automation strategy.
- Set and enforce high standards for experimentation, statistical rigour, measurement and uncertainty communication to stakeholders.
- Mentor and influence other data scientists, advocating for robust, maintainable solutions.

Requirements:
- Significant commercial experience building and shipping production ML systems and Generative AI/LLM solutions.
- Strong statistical foundations and experience designing experiments and evaluating model performance.
- Proven system-level thinking: architecture, monitoring, feedback loops and maintainability in production environments.
- Track record of influencing cross-functional technical direction and communicating with senior stakeholders.
- Comfortable working with engineering teams to deploy, monitor and operate models; product-minded and outcome-focused.

Responsibilities

Provide technical leadership for data science in claims and fraud, focusing on scaling decisioning and automating the claims journey. Design and deploy production-grade machine learning and generative AI systems while collaborating with cross-functional teams to ensure robust, scalable solutions.

Requirements

Requires significant commercial experience in end-to-end machine learning and hands-on experience shipping generative AI systems in production. Candidates must possess a strong statistical foundation and proven ability to influence technical direction across data science and engineering teams.

Key skills

• Machine Learning — in 291 other listings on The Stack
• Generative AI — in 58 other listings on The Stack
• LLM — in 51 other listings on The Stack
• Risk decisioning — not in any other listing on The Stack
• Fraud detection — in 10 other listings on The Stack
• System-level thinking — in 3 other listings on The Stack
• Statistical rigour — in 1 other listing on The Stack
• Data science — in 86 other listings on The Stack
• Stakeholder management
• Production deployment
• Technical leadership
• Automation
• Product strategy
• Engineering collaboration
• Model integration

On The Stack (as of 2026-11-05)

• marshmallow has 5 other listings on The Stack, 5 of them marked as offering visa sponsorship.
• 214 visa-sponsored jobs in the United Kingdom on The Stack, posted in the last 60 days.
• 68 visa-sponsored data scientist jobs in Europe on The Stack, posted in the last 60 days.

Frequently asked questions about marshmallow

Is this Staff Data Scientist role still open?

It was posted on 2026-10-06 and is listed as active on The Stack. Confirm on marshmallow's application page before applying.

Does marshmallow offer visa sponsorship?

This listing is marked as offering visa sponsorship. Eligibility rules are set by the employer, so check the details on marshmallow's site.

Where is this role located?

The listing gives the location as London, United Kingdom. It is marked hybrid.

What skills does this role ask for?

The listing names: Machine Learning, Generative AI, LLM, Risk decisioning, Fraud detection, System-level thinking, Statistical rigour, Data science, Stakeholder management, Production deployment, Technical leadership, Automation, Product strategy, Engineering collaboration, Model integration.