Data & AI Science Consultant

Overview

In this role, you will apply advanced machine learning and analytics to solve real business problems for clients. You collaborate with cross-functional teams to turn data into actionable insights and scalable AI solutions. You’ll work on discovery analytics, model development, and deployment, helping clients realise value from Data & AI at scale. The opportunity combines hands-on technical work with client-facing leadership and continuous learning in a global, innovative environment.

Pay / Benefits

• 30 days vacation per year
• gym subsidy
• private medical insurance
• 3 extra days leave for charitable work

Responsibilities

• Solve business problems using advanced ML methods (e.g., deep learning, quantitative analytics)
• Understand requirements and support business case development
• Conduct discovery analytics to identify opportunities
• Partner with developers to deploy ML algorithms delivering business value
• Define approaches to embed and scale ML models
• Build reusable assets and best practices for future problems
• Consult on complex analyses and advanced ML methods
• Communicate with senior client leadership and teams
• Contribute data science expertise to sales activities
• Shape DS strategy and DS solution delivery
• Operate across multiple industries/functions
• Develop others by sharing knowledge and skills

Key requirements

• Relevant work experience in data science, ML, and business analytics
• Coding experience (Python preferred; R, Scala)
• Proficiency with SQL, ETL, No-SQL, DW; Big Data tech (pySpark, Hive)
• Experience with structured and unstructured data (text, PDFs, images, video)
• Knowledge of ML modeling techniques and fine-tuning (XGBoost, DNNs, Transformers, Markov chains)
• Experience with ML libraries (Fastai, Keras, TensorFlow, PyTorch, scikit-learn, huggingface)
• Ability to learn new techniques and implement them
• Cloud experience (AWS, GCP, Azure)
• Specialised visualization techniques (D3.js, ggplot)
• Strong verbal/written communication & data presentation
• Awareness of Large Language Models (LLMs) and ongoing learning

• Strong communication and presentation skills
• Client relationship building
• Problem solving and solution orientation
• Python
• R
• Scala

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