Role: Associate Director - AI & Machine Learning

Rate: Neg

Location: London (2-3 days a week on site)

Status: Inside IR35

Term: Initial 6 months

Our client, a growing digital and AI consulting practice, is looking for an Associate Director to lead the delivery of advanced AI and machine learning solutions across a range of industries.

This is a senior, hands-on role combining technical leadership, client engagement, and commercial delivery, with a strong focus on causal AI and real-world impact.

The Role

You will lead end-to-end AI engagements, from shaping problem statements through to production deployment. This includes designing scalable ML systems, guiding delivery teams, and ensuring high technical standards across projects.

A key part of the role is applying causal inference techniques to solve complex business problems, moving beyond prediction to understanding cause-and-effect.

Key Responsibilities

• Lead delivery of AI/ML solutions from design through to production
• Architect systems across ML, NLP/LLMs (eg RAG), and knowledge graphs
• Act as the senior technical lead, ensuring quality, scalability, and best practice
• Translate business problems into structured technical solutions
• Manage and mentor data scientists and engineers
• Apply causal modelling to areas such as churn, pricing, and optimisation
• Support business development, proposals, and technical assessments

Required Experience

Causal AI (Essential)

• Strong hands-on experience with causal inference (eg DoWhy, EconML)
• Building and interpreting causal models (DAGs) in real-world scenarios
• Experience estimating treatment effects using observational data
• Ability to clearly explain causal vs predictive approaches

Machine Learning & AI

• Strong Python experience (Pandas, NumPy, Scikit-learn, PySpark)
• Experience with LLM systems (RAG, prompt engineering, orchestration frameworks)
• Knowledge graphs (Neo4j or similar)
• End-to-end ML life cycle experience (MLOps, CI/CD, MLFlow, Docker, etc.)

Consulting & Commercial

• Background in consulting or client-facing delivery roles
• Experience handling stakeholders and translating complex requirements
• Exposure to due diligence or value creation work is beneficial

Ideal Background

• Experience in financial services, private equity, or regulated industries
• Strong academic background in a quantitative field (MSc/PhD preferred)
• Exposure to real-world AI deployments and measurable business impact