Lead Data Scientist

 

Why Valtech? We’re the experience innovation company - a trusted partner to the world’s most recognized brands. To our people we offer growth opportunities, a values-driven culture, international careers and the chance to shape the future of experience.

 

The opportunity

At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries.

 

We are proud of:

• The work we do and innovation we drive
• Our Values of share, care and dare
• A workplace culture that fosters creativity, diversity and autonomy
• Our borderless, global framework, which enables seamless collaboration

 

The Role:

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

 

Must have Qua