At a Glance
- Tasks: Lead AI and machine learning projects, from design to deployment, making a real-world impact.
- Company: Dynamic digital and AI consulting practice in London.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Mentorship opportunities and a collaborative environment await you.
- Why this job: Join a cutting-edge team and shape the future of AI solutions across industries.
- Qualifications: Expertise in causal AI, strong Python skills, and experience in client-facing roles.
The predicted salary is between 80000 - 100000 € per year.
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
Associate Director - AI & Machine Learning in London employer: Synergetic
Join a dynamic and innovative digital and AI consulting practice in London, where you will have the opportunity to lead cutting-edge AI and machine learning projects that drive real-world impact. Our collaborative work culture fosters continuous learning and professional growth, with a strong emphasis on mentorship and technical excellence. Enjoy the unique advantage of working in a vibrant city while being part of a forward-thinking team dedicated to pushing the boundaries of technology.
StudySmarter Expert Advice🤫
We think this is how you could land Associate Director - AI & Machine Learning in London
✨Tip Number 1
Network like a pro! Get out there and connect with people in the AI and machine learning space. Attend meetups, webinars, or industry events to meet potential employers and showcase your expertise.
✨Tip Number 2
Showcase your skills! Create a portfolio of your projects, especially those involving causal AI and machine learning. This will give you a tangible way to demonstrate your capabilities during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python skills and understanding causal inference techniques. Be ready to discuss your past experiences and how they relate to the role you're applying for.
✨Tip Number 4
Don’t forget to apply through our website! We’re always looking for talented individuals like you, and applying directly can sometimes give you an edge over other candidates.
We think you need these skills to ace Associate Director - AI & Machine Learning in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of Associate Director - AI & Machine Learning. Highlight your experience with causal AI and machine learning, and don’t forget to showcase any relevant projects that demonstrate your hands-on skills.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re the perfect fit for this role. Mention specific experiences that align with the job description, especially around leading AI engagements and applying causal inference techniques.
Showcase Your Technical Skills:Since this role requires strong technical leadership, make sure to highlight your proficiency in Python and any experience with ML systems, NLP, or knowledge graphs. We want to see how you can lead teams and ensure high technical standards!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Synergetic
✨Know Your Causal AI Inside Out
Make sure you brush up on causal inference techniques, especially tools like DoWhy and EconML. Be ready to discuss how you've applied these in real-world scenarios, as this role heavily focuses on understanding cause-and-effect.
✨Showcase Your Technical Skills
Prepare to demonstrate your hands-on experience with Python and machine learning libraries like Pandas and Scikit-learn. You might be asked to solve a technical problem on the spot, so practice coding challenges related to ML systems and knowledge graphs.
✨Engage with Real-World Applications
Think of specific examples where you've led AI/ML projects from design to deployment. Be ready to explain how your solutions have had measurable business impacts, particularly in areas like churn or pricing optimisation.
✨Communicate Clearly with Stakeholders
Since this role involves client engagement, practice explaining complex technical concepts in simple terms. Prepare to discuss how you've managed stakeholder expectations and translated their needs into structured technical solutions.
