Senior Data Scientist
Artefact · 17th Floor, 5 Aldermanbury Square, London, EC2V 7HR · 2026-09-04
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.
• Programming & Data Engineering: Proficiency in object-oriented Python, advanced dataframes (Polars/Pyspark), and data versioning (DVC). Experience designing data storage solutions and using object-oriented SQL interfaces.
• Cloud & DevOps: Hands-on experience with at least two major cloud providers (AWS, Azure, GCP), including app deployment, database services (e.g., RDS, CosmosDB), and infrastructure-as-code (Terraform). Solid understanding of CI/CD for testing and containerisation.
Desirable experience
• Advanced Education: A Master's degree or PhD in a relevant field is a strong plus.
• Parallelisation & Performance: Experience with parallelisation frameworks like Pyspark or Ray.
• Advanced Cloud & Infrastructure: Familiarity with serverless deployments (e.g., Fargate, Lambdas), infrastructure automation with Terratest or Ansible.
Skills asked for
- agile
- data science
- machine learning
- nlp
- python
- devops
- aws
- azure
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