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Senior Data Scientist
Job in
City Of London, Central London, Greater London, England, UK
Listed on 2026-09-22
Listing for:
Artefact
Full Time
position Listed on 2026-09-22
Job specializations:
-
IT/Tech
Data Engineering, Data Scientist, Machine Learning/ ML Engineer, AI Engineer (Applied/Software)
Job Description & How to Apply Below
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 data frames (Polars/Pyspark), and data versioning (DVC). Experience designing data storage solutions and using object-oriented SQL interfaces. - Cloud & Dev Ops
:
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.
Position Requirements
10+ Years
work experience
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