Lead Data Scientist - Agentic AI / AML at Wise

✨ The Stack take on this Wise job

• 🏢 Wise has 49 jobs here, 47 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 Wise 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 design, development and deployment of LLM and agentic AI solutions to automate AML handling (case summaries, red flags, risk classification, document requests, agentic workflows).
- Define labeling taxonomies and build evaluation datasets and automated evaluation pipelines to measure accuracy, precision, recall and failure modes.
- Run prompt optimisation and structured experiments (few-shot, chain-of-thought, context ordering) to reduce hallucinations and prompt drift.
- Architect agentic workflows that safely chain reasoning, tool use and contextual data.
- Implement shadow testing, monitoring and post-deployment evaluation to track performance and drift.
- Drive technical strategy, mentor data scientists, and embed robust ML/LLM best practices across the team.

Requirements:
- Strong production experience with Python and building ML/LLM-powered workflows and pipelines.
- Deep knowledge of generative AI, LLM evaluation, prompt engineering and experiment design.
- Experience designing agentic AI systems, monitoring, human-in-the-loop controls and safety mitigations.
- Familiarity with OOP best practices and tools like LangGraph; experience with evaluation frameworks and labeling.
- Background or exposure to AML/financial crime operations and operational tooling is highly desirable.
- Strong communication, product focus and ability to lead cross-functional technical initiatives.

Responsibilities

Lead the development and deployment of AI models and agentic workflows to automate anti-money laundering operational tasks. Drive technical strategy, mentor team members, and establish robust evaluation frameworks to ensure the accuracy and reliability of AI-driven financial crime mitigation.

Requirements

Requires strong experience in implementing and evaluating machine learning systems, specifically with Python and LLM-powered workflows. Candidates should possess a product-focused mindset and the ability to lead complex technical initiatives in a cross-functional environment.

Key skills

• Python — in 1200 other listings on The Stack
• Generative AI — in 58 other listings on The Stack
• LLMs — in 80 other listings on The Stack
• Agentic AI — in 39 other listings on The Stack
• Machine Learning — in 291 other listings on The Stack
• Prompt Engineering — in 59 other listings on The Stack
• Financial Crime Mitigation — in 1 other listing on The Stack
• Data Science — in 86 other listings on The Stack
• Statistical Analysis
• Experiment Design
• Technical Leadership
• Automation
• Evaluation Frameworks
• OOP Principles
• LangGraph

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

• Wise has 48 other listings on The Stack, 46 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 Wise

Is this Lead Data Scientist - Agentic AI / AML role still open?

It was posted on 2026-11-04 and is listed as active on The Stack. Confirm on Wise's application page before applying.

Does Wise offer visa sponsorship?

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

Where is this role located?

The listing gives the location as United Kingdom. It is marked on-site.

What skills does this role ask for?

The listing names: Python, Generative AI, LLMs, Agentic AI, Machine Learning, Prompt Engineering, Financial Crime Mitigation, Data Science, Statistical Analysis, Experiment Design, Technical Leadership, Automation, Evaluation Frameworks, OOP Principles, LangGraph.