Principal Consultant – AI & Data Science

Role overview

Core responsibilities

• Lead end-to-end enterprise AI, machine learning and data science project delivery.
• Identify business opportunities where AI can solve meaningful problems.
• Lead multidisciplinary data and technology delivery teams.
• Design scalable solutions for analytics, forecasting, recommendation systems, NLP and Generative AI.
• Guide clients through the full machine learning lifecycle.
• Design AI architectures using Azure, Databricks and Snowflake.
• Establish MLOps, Responsible AI, model governance and AI operating models.
• Lead workshops, architecture reviews and executive steering committees.
• Support pre-sales, RFx responses, proposals and solution estimation.
• Mentor consultants and technical specialists and contribute to reusable assets.

Essential experience

• Have 12+ years of experience delivering enterprise Data Science, Machine Learning or AI solutions.
• Have led complex AI projects from business problem definition through production deployment.
• Have strong consulting experience with enterprise clients and executive stakeholders.
• Have led multidisciplinary teams across data science, machine learning, data engineering and architecture.
• Balance technical leadership with commercial outcomes and client relationship management.
• Have personally built and delivered AI solutions rather than only advising on AI strategy.

Technical expertise

• Practical experience across several areas including machine learning, statistical modelling, predictive analytics, forecasting, optimisation and recommendation engines.
• Experience with NLP, deep learning, feature engineering, model evaluation, production AI systems, MLOps, monitoring and governance.
• Practical Generative AI experience may include LLMs, RAG, orchestration, prompt engineering, vector databases and agentic architectures.
• Technology experience may include Python, SQL, Spark, Databricks, Azure AI, Azure Machine Learning, Snowflake, MLflow, Git, CI/CD and Docker.

Highly desirable

• Master's or PhD in computer science, statistics, mathematics, data science or a related quantitative discipline.
• Relevant Azure, Databricks or Snowflake certifications are highly desirable.
• Experience with enterprise MLOps, Responsible AI governance or regulated industries is highly desirable.
• Open-source contributions, publications or conference presentations are highly desirable.

Workplace type

• Hybrid working.

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