Junior Engineer

Artefact
17th Floor +3 more
Career-pivot friendly

Who this role is best for

Geared toward recent graduates or early-career professionals comfortable with collaborative engineering projects and upskilling in AI and data technologies, based in London with a hybrid work arrangement.

Best fit for

  • Recent graduates with a strong foundation in data science and a desire to grow through training and mentorship
    — “training and certification to enhance your skills in software engineering, data science, and data architecture”
  • Candidates with a quantitative background and interest in working on diverse business domains
    — “Education: A Bachelor's or Master’s degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related quantitative field.”
  • Individuals who thrive in team-based environments and are open to learning from senior engineers
    — “the ability to work effectively in a team environment and learn from senior members”

Things to consider

  • The role requires a commitment to in-person work at least part of the time in London
    — “Hybrid working pattern”
  • A Master's or PhD is not mandatory but may be a differentiator in the selection process
    — “A Master's degree or PhD in a relevant field is a strong plus”

How to stand out

  • Highlight your ability to break down complex problems and demonstrate analytical thinking in your resume
    — “an analytical mindset with the ability to break down complex problems into manageable steps”
  • Showcase hands-on projects or coursework that reflect your eagerness to learn and adapt to new technologies
    — “a genuine passion for technology and a proactive attitude towards self-development and learning new skills”
  • Emphasize any experience with Git or CI/CD in your technical skills section
    — “demonstrable understanding of version control and repository tools (Git, CI/CD)”
  • Include examples of clean, well-documented code in your portfolio or resume
    — “commitment to writing clean, well-documented code”
  • Demonstrate your SQL proficiency with concrete examples of database querying experience
    — “Experience with SQL for querying relational databases”
Pace · SteadyCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • engineering projects
  • training and certification
Typical background
Bachelor's or Master’s degree in Computer Science or related field

Skills & requirements

Required

Programming ProficiencySoftware Engineering FundamentalsData SkillsProblem-solvingCommunication

Preferred

Cloud Platform ExposureCore ML KnowledgeAdvanced Education

Stack & domain

PythonSQLVersion ControlRepository ToolsClean CodeCloud PlatformContainerizationMachine Learning ConceptsProblem SolvingCommunicationTeamworkLearningSoftware EngineeringData ScienceData Architecture

About the role

Original posting from Artefact via Greenhouse

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 1,700 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 members

training 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 & 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 & 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.

Hybrid working pattern 

Source: Artefact careers (Greenhouse)

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