Junior Engineer

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 1,700 employees operate in 25 countries (Americas, Europe, Asia, Middle East, India, Africa) and we partner with 1,000+ clients. As a Junior Software Engineer in our London office, your role will encompass working on engineering projects together with senior team members and training and certification to enhance your skills in software engineering, data science, and data architecture.

Responsibilities

Working on engineering projects together with senior team members; Training and certification to enhance your skills in software engineering, data science, and data architecture

Requirements

Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related quantitative field; Strong programming skills in Python and a solid understanding of data structures and algorithms; A demonstrable understanding of version control and repository tools (Git, CI/CD) and a commitment to writing clean, well-documented code; Experience with SQL for querying relational databases; An analytical mindset with the ability to break down complex problems into manageable steps; A genuine passion for technology and a proactive attitude towards self-development and learning new skills, as demonstrated through projects or coursework; Strong verbal and written communication skills, with the ability to work effectively in a team environment and learn from senior members

Nice to have

Basic familiarity with a cloud platform (AWS, GCP, or Azure) and an awareness of concepts like containerization (Docker); A good grasp of fundamental machine learning concepts, including supervised/unsupervised learning, model evaluation techniques, and feature engineering; A Master's degree or PhD in a relevant field is a strong plus