Lead AI Data Scientist

Proactive Appointments; City Of London; Hybrid; GBP 80,000 - 140,000; Full time

Benefits offered by this job

Hybrid work model

Pension 4% matched

Life cover 3x

Cash plan

Sick pay

Job summary

Proactive Appointments is recruiting a Lead AI Data Scientist to head the data science programme, prototype AI solutions, and drive production deployment within a hybrid UK-based team.

You will recruit and lead a small team, work with SMEs and engineers, and monitor AI workflows to ensure ongoing performance and measurable impact. This role offers a strong salary and extensive benefits.

Qualifications

• ≥5 years as a data scientist with leadership or directional experience.
• Experience taking models from prototype to production and monitoring.
• Hands-on with LLMs, prompt design, and retrieval-augmented generation.
• Ability to define AI system architecture and success metrics.

Responsibilities

• Lead data science work within the programme and guide production deployment.
• Mentor and hire, build a growing data science team.
• Collaborate with SMEs, analysts and engineers to identify automation opportunities.
• Monitor AI-enabled workflows and drive continuous improvement.

Skills

Data science leadership

LLM prototyping

Prompt design

Python

SQL

Cloud platforms

Stakeholder management

Tools

Azure

Databricks

Snowflake

Job description

Lead AI Data Scientist

Our client is urgently looking for an experienced Lead AI Data Scientist, with good demonstrable experience with AI to join their team on an 18-month Fixed-Term basis.

Our client is looking to get AI embedded at scale – a more structured and measurable manner, into the delivery of our client’s services across the group.

This is a new role created to lead data science within that programme. Working closely with Subject Matter Experts (SMEs), business analysts and engineers, you’ll identify where within legal workflows automation/AI can deliver the greatest benefits, prototype solutions and guide them into Production. Once in use, you’ll then help to monitor them to ensure they continue to perform.

Finally, you will be the founding member of the Data Science team but there is a lot to do so one of your first tasks will be to recruit a colleague to work for and alongside you. So this is also an excellent opportunity to build and manage a small, and hopefully, growing team.

You will be rewarded with an excellent salary, as well as a brilliant benefits package including, hybrid 2 days on-site, pension scheme (4% matched), 3x life cover, cash plan, sick pay, salary sacrifice and many, many more perks!

Lead AI Data Scientist – Key Skills:

• Substantial experience (5+ years) as a data scientist, including time leading or setting direction for data science work, with a track record of taking models from prototype into Production and keeping them running.
• Experience managing, mentoring, or informally leading data scientists or analysts, including supporting hiring, setting priorities, and developing others, or a demonstrated interest in moving into people management.
• Hands-on building and evaluating LLM-based solutions, including prompt design, retrieval-augmented generation, and structured evaluation approaches such as human-in-the-loop review and LLM-as-Judge.
• Collaborating to define AI system architecture and design, along with emerging techniques such as MCP, agent skills, AI harness design and context engineering.
• Definition of success metrics and baselines for a programme or product, and designing before-and-after analysis to show measurable impact, ideally in terms the business cares about (productivity, quality, cost, margin).
• Monitoring models or AI-enabled workflows in Production and identifying quality degradation or drift, with the ability to recommend and drive fixes.
• Strong data skills: assessing data quality and fitness for purpose across multiple source systems, mapping how data moves between them, and contributing to target data models. Proficiency in Python and SQL, and experience working on a cloud data platform (e.g. Azure, Databricks, Snowflake).
• Built dashboards and automated reporting for non-technical stakeholders.
• Worked closely with engineers and architects to define paths to Production, including cost-to-run considerations such as consumption, licensing and cost per task.
• Ability to effectively leverage AI coding tools to accelerate prototyping, experimentation and development.
• Strong stakeholder skills: the ability to work with subject matter experts and business analysts, translate

Lead AI Data Scientist

Due to the volume of applications received for positions, it will not be possible to respond to all applications and only applicants who are considered suitable for interview will be contacted.

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