# Senior Data Scientist at Artefact

> United Kingdom · Senior · Analytics / Data science · open. Source: https://alderhq.app/jobs/greenhouse%3Aartefact%3A8422392002 (read 2026-11-05).

## Facts (observed)

- Company: [Artefact](https://alderhq.app/companies/artefact)
- Location text: 17th Floor, 5 Aldermanbury Square, London, EC2V 7HR; London
- Where it can be done from (inferred): United Kingdom (evidence: "Location: 17th Floor, 5 Aldermanbury Square, London, EC2V 7HR; London")
- Posted: 2026-02-13 (265 days ago)
- First seen by alder: 2026-11-02 · last verified: 2026-11-04
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://job-boards.greenhouse.io/artefact/jobs/8422392002
- Skills listed (inferred): Python, AWS, GCP, Azure, Terraform, SQL

## Pay and sponsorship

- Posted pay: not posted
- Market band for similar posted roles (London, n 4): p25 £80k, median £96k, p75 £109k

## Description (the employer's text)

### 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.

---
Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Aartefact%3A8422392002 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.