---
title: 'Senior Data Scientist at Artefact'
canonical: 'https://feeny.ai/job/senior-data-scientist-artefact-london-tzjsewrmky2g'
type: 'job'
last_seen: '2026-09-10'
---

# Senior Data Scientist at Artefact

- **Company:** Artefact
- **Location:** London, United Kingdom
- **Posted:** 2026-02-13
- **Last confirmed live:** 2026-09-10
- **Apply:** https://job-boards.greenhouse.io/artefact/jobs/8422392002

## Job description

## 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.

## About Artefact

##

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