Senior Data Scientist

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.