img
Permanent

Junior Software Engineer

City of London
money-bag Negotiable
74AD6D2F246F39175A3B9AF7FC1DF707
Posted Today

1st Floor The Rex Building, 62-64 Queen Street, London, England, EC4R 1EBWho 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

1,700 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

Junior Software Engineer

in our

London office , your role will encompass:working on engineering projects together with senior team memberstraining and certification to enhance your skills in software engineering, data science, and data architecture.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.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 and Collaboration:

Strong verbal and written communication skills, with the ability to work effectively in a team environment and learn from senior members.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.

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