Artefact
Senior Data Scientist
● Verified active
- Location
- 17th Floor, 5 Aldermanbury Square, London, EC2V 7HR
- Last checked
- Oct 26, 2026
About this role
Who we are
- Artefact is a leading global consulting firm dedicated to accelerating the adoption of data and AI. We work with a variety of businesses, from supermarket chains, to private equity firms and telecoms; including Nissan, L'Oréal, Carrefour, WHSmith, Orange, Beiersdorf, BNP Paribas, and Samsung.
- Our success stems from combining advanced data technologies, agile methods for quick delivery, and dedicated teams of data scientists, data engineers, business consultants, and data analysts.
- Our 1,800 employees operate in 25 countries (Americas, Europe, Asia, Middle East, India, Africa) and we partner with 1,000+ clients.
What you will be doing
As a Senior Data Scientist in our London office, your role will encompass:
- Designing and implementing advanced data science and machine learning solutions to solve complex business problems.
- Taking ownership of project streams, from defining technical deliverables and timelines to presenting updates to client steering committees.
- Supervising and mentoring team members on code, deployment, and best practices.
- Architecting and deploying robust, scalable solutions using modern cloud technologies and MLOps principles.
Qualifications
Necessary education and experience
- Education: A Bachelor's or Master’s degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related quantitative field.
- Project & Team Leadership: Demonstrable experience supervising team members, taking responsibility for project delivery, defining technical tasks, and presenting project updates to both internal and client stakeholders.
- Advanced Modelling: Proven ability to implement a range of complex models such as time-series forecasting, gradient boosting, clustering, NLP, and Bayesian inference.
- ML-Ops & Orchestration: Strong experience with MLOps tools for orchestration, experiment tracking, hyper-parameter tuning, and deploying automated model retraining pipelines.