Lead Data Scientist
Role details
Job location
Tech stack
Job description
As a Lead Data Scientist, you bring strong commercial experience applying data science to solve real-world business challenges. You are comfortable working across classical machine learning and emerging AI techniques, particularly in LLM/Agentic AI space.
You can move between hands-on modelling, exploring new approaches (e.g. LLMs), and explaining insights clearly to non-technical stakeholders. With a pragmatic, problem-solving mindset, you help shape opportunities and deliver impactful solutions.
You will thrive in this role if you are:
- A curious problem solver who challenges the status quo
- Comfortable bridging the gap between technical data science and client business needs
- Passionate about innovation and exploring "what's next" in AI and ML
- Experienced in working within Agile methodologies and consultancy environments
- Keen to take ownership while supporting and guiding others
Role Responsibilities:
Data Science, AI & Delivery
- Work with structured and unstructured data to support model development and analysis
- Design and implement ML and AI solutions, including LLM-based and traditional approaches
- Apply techniques such as RAG, embeddings, and fine-tuning where appropriate
- Contribute to development and optimization of AI applications using established and emerging agentic patterns (e.g. tool use, orchestration, multi-step reasoning)
- Apply evaluation frameworks to assess model and system performance
- Contribute to deploying models and supporting them in production using engineering and MLOps best practices
- Stay up to date with emerging AI techniques and experiment with new approaches, tools, and frameworks
Problem Scoping & Client Engagement
- Translate business questions into clear data science approaches
- Communicate results and insights to technical and non-technical stakeholders
- Contribute to identifying opportunities where data science and AI can add value
- Support project scoping and provide guidance to less experienced team members when needed
Requirements
- 5+ years of experience in Data Science or Analytics
- Strong foundation in machine learning and predictive modelling
- Exposure to Generative AI concepts (e.g. LLMs, RAG, fine-tuning, prompt engineering)
- Strong programming skills in Python and SQL
- Familiarity with cloud-based solutions (e.g. GCP, Azure, AWS)
- Experience working with real-world, production data problems
- Ability to communicate technical concepts clearly to non-technical stakeholders, * Experience in consulting or client-facing environments
- Hands-on experience designing and deploying Generative AI solutions, including Agentic AI systems.
- Experience with MLOps practices and taking models into production environments
- Exposure to modern data engineering practices and integration with data pipelines
- Awareness of Responsible AI practices (bias, evaluation, safety)