Salary
≈ $83k – $163k per year (Estimated)
Location
In office (London)
Seniority
Senior
Visa
Licensed UK visa sponsor
Confirmed on the employer's own hiring board on Nov 4, 2026. First seen by Alion on Feb 13, 2026. Artefact scores B on the Alion truth index.
Overview
Company
Impact
Profile match
Artefact is a French data and artificial intelligence consultancy founded in 2015 that works on marketing, commercial and operational problems for large consumer-facing companies. Its distinguishing feature is combining data science with marketing execution: it builds the data platforms and models and then runs the campaigns and commerce operations they inform, rather than handing recommendations to an agency. Headquartered in Paris with offices across Europe, Asia, the Middle East and North America, it was taken private by Ardian in 2023 and employs several thousand consultants and data specialists.
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.
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