Junior Engineer (Graduate)

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 Graduate **Junior Engineer** in our **London office starting in September 2026**, your role will encompass: - working on engineering projects together with senior team members - training and certification to enhance your skills in software engineering, data science, and data architecture. ## Qualifications ### Necessary education and experience - **Education:** You will be graduating in **2026** with a Bachelor's or Master’s degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related quantitative field. - **Programming Proficiency:** Strong programming skills in **Python** and a solid understanding of data structures and algorithms. - **Software Engineering Fundamentals:** A demonstrable understanding of version control and repository tools (Git, CI/CD) and a commitment to writing clean, well-documented code. - **Data Skills:** Experience with SQL for querying relational databases. - **Problem-Solving Skills:** An analytical mindset with the ability to break down complex problems into manageable steps. - **Eagerness to Learn:** A genuine passion for technology and a proactive attitude towards self-development and learning new skills, as demonstrated through projects or coursework. - **Communication & Collaboration:** Strong verbal and written communication skills, with the ability to work effectively in a team environment and learn from senior members. ### Desirable experience - **Cloud and MLOps Exposure:** Basic familiarity with a cloud platform (AWS, GCP, or Azure) and an awareness of concepts like containerization (Docker). - **Core ML Knowledge:** A good grasp of fundamental machine learning concepts, including supervised/unsupervised learning, model evaluation techniques, and feature engineering. - **Advanced Education**: A Master's degree or PhD in a relevant field is a strong plus.