Experience designing data storage solutions and using object-oriented SQL interfaces.
Solid understanding of CI/CD for testing and containerisation.
Qualification wording
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.
Education & alternatives
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.
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.
Tools in this posting
Python
SQL
AWS
Azure
GCP
Terraform
Polars
PySpark
Source — Tool mentions in context
- 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.
- 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
Artefact is a leading global consulting firm dedicated to accelerating the adoption of data and AI.
Open 6 monthsWe first saw this posting 204 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
Status in our records
Live
First seen by us
Apr 15, 2026204 days ago
Recorded sightings
135
Last seen by us
Nov 5, 2026
Apr 15, 2026today
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 204
756
Up longer than most. Similar jobs usually come down between day 7 and day 56.
Well past Artefact’s usual: its jobs come down by about day 36.
From 10,289 similar postings that came down, and 27 of Artefact’s. Coming down is not always a hire.
Artefact is hiring
46 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Check the employer’s posting for the current role and application details.
Applying through Greenhouse
No account needed: the form is one page, with an “Autofill my application” option that reads your resume.
Greenhouse doesn’t read resumes over 2.5 MB, or details placed in a header, footer, text box, table or second column. The file still attaches, but a recruiter has to type you in by hand.
Yes. We’ve followed 2 other Senior Data Scientist jobs there since March 2026. All 2 are still up.
ParisStill up after 230 days, first seen Mar 21
JakartaStill up after 205 days, first seen Apr 14
This jobUp 205 days so far, first seen Apr 15
Mar 21Today
Demand for Data Scientist roles
New Data Scientist postings at the employers we follow are down 3% over the last 5 weeks compared with the 5 before.
August 17Last week
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
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.