Role overview
We are seeking an exceptional Senior Data Scientist to join us full-time in our Artificial Intelligence (AI) Practice Team, Europe. In this role, you will lead the design and delivery of analytics and machine learning solutions across policy, data, and document-centric AI engagements, working with complex real-world datasets from industrial and asset-intensive domains. You will partner closely with consultants, domain experts, and junior data scientists to turn client data into robust models, reusable assets, and decision-ready insights. Based in Warrington or London England with some remote flexibility, you will help shape our technical approaches, uplift data science practices, and ensure solutions are production-aware and business-relevant.
What you'll work on
- Lead the preparation, exploration, and analysis of client data (tabular, time-series, and document-based) to enable robust modeling, feature engineering, and insight generation.
- Design, implement, and validate machine learning models and analytics pipelines, including problem framing, model selection, evaluation, and iteration for real-world performance.
- Drive advanced use of NLP and document understanding techniques to extract, transform, and enrich information from reports, PDFs, logs, and other unstructured sources.
- Build and maintain clear, impactful dashboards, reports, and visualizations (e.g., in Python, Power BI, or similar tools) to communicate findings to consultants and client stakeholders.
- Collaborate with consultants and domain experts to translate business problems into analytical solutions, articulate trade-offs, and present recommendations to technical and non-technical audiences.
- Ensure technical quality, reproducibility, and governance by establishing good practices for code, documentation, data management, and model tracking across projects.
- Mentor and support junior data scientists, providing guidance on methods, tooling, and best practices, and reviewing their work for quality and consistency.
What we're looking for
Education and Experience
- Bachelor’s degree in a STEM discipline (e.g., Data Science, Computer Science, Engineering, Mathematics, Statistics) or related field; Master’s degree preferred or equivalent experience.
- 5+ years of experience applying data science and machine learning in professional settings, including end-to-end delivery of analytics/ML solutions.
- Proven track record working with real-world, messy datasets (including unstructured/document data) across the full lifecycle: data preparation, modeling, evaluation, and deployment handoff.
- Experience leading or owning significant workstreams within AI/ML or analytics projects, ideally in consulting, industrial, or asset-intensive environments.
- Practical experience working with cloud-based and modern data platforms (e.g., Azure, AWS, GCP, Databricks) and integrating with enterprise data sources and workflows.
Knowledge, Skills, and Abilities