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