Junior Data Scientist

About Immensa

Immensa is transforming spare parts supply chains through digital warehousing and advanced manufacturing. We help energy and industrial clients assess, digitize, and manufacture spare parts on demand by combining AI-powered inventory assessment, 3D scanning, reverse engineering, and supplier selection optimisation.

Through

Immensa360, our proprietary digital warehousing platform, we enable clients to securely manage digital spare parts and access localized production significantly reducing manufacturing costs and lead time.

About the role

We are looking for a Junior Data Scientist to join our AI & Technology team at Immensa.

This is a hands-on role for a technically strong early-career candidate who is excited by solving real-world industrial problems.

This is not a narrow, siloed data science role, our team is technology agnostic - we choose the best tools for the product and problem at hand. While our foundations are rooted in Python for data analytics and machine learning, we are not constrained by a single language or framework. We use GenAI-assisted development to move fluently across the stack, translating ideas into the technologies best suited for building and deploying production ready solutions

— whether that is Python, cloud-native services, or modern application frameworks such as

Next.js for local or cloud-hosted products.

We are not looking for someone who simply relies on AI to generate output, we are looking for someone with strong enough technical foundations to understand what they are building,

validate it, improve it, and dive into the detail when needed.

What you will do • Build and improve data, AI, and software solutions that support Immensa’s digital warehousing and advanced manufacturing workflows.

• Work on problems spanning data engineering, automation, predictive modelling, and application development.
• Prototype quickly, test ideas with stakeholders, and iterate solutions into robust products for both operations and customers.
• Support development of workflows related to spare parts digitization, reverse engineering, data capture, engineering operations, and manufacturing processes.
• Collaborate closely with engineering, digitization, production, supply chain, and commercial teams.

Who we are looking for

We are looking for someone who is bright, curious, and highly capable at solving difficult problems. You should be comfortable operating in a startup environment where speed,

ownership, adaptability, and communication matter just as much as technical skill.

You do not need to have years of industry experience, but you do need to demonstrate strong technical fundamentals and a clear ability to build.

Must-haves • Bachelor’s degree in Data Science, Computer Science, Engineering, Mathematics,

Physics, or a related technical discipline.

• Strong foundations in Python and SQL.
• Proven experience applying data pipelines, data analytics, and machine learning to solve real problems.
• Experience with version control, CI/CD, APIs, Docker, or software deployment workflows.
• Experience working with clouds service providers (AWS, Azure).
• Experience using GenAI coding tools productively and responsibly as part of a development workflow.
• Confidence debugging issues and learning new tools quickly.
• Strong analytical and problem-solving ability.
• Ability to build, deploy, and maintain working solutions, not just POC's.
• Strong communication and stakeholder management skills.
• Proactive, independent mindset with the ability to take a problem, shape a solution,

and move it forward.

• Comfortable receiving feedback, iterating quickly, and keeping stakeholders engaged throughout delivery.

Nice to have • Experience building or using MCP-enabled tools, agent skills, and multi-tool AI workflows to create capable, context-rich agents.

• Master degree in in Data Science, Machine Learning, or AI.
• Time in industry via internships or graduate schemes.
• Projects related to manufacturing, mechanical engineering, 3D scanning, CAD, digital twins, additive manufacturing, reverse engineering, or industrial operations.
• A GitHub, portfolio, or project repository that demonstrates technical initiative.

What will make you successful in this role • You can take an ambiguous problem and structure it clearly.

• You are comfortable switching between analysis, coding, experimentation, and stakeholder discussion.
• You move quickly, but you care about quality and correctness.
• You use AI tools to multiply your productivity, while still understanding the technical details behind what you build.
• You enjoy learning across disciplines and are motivated by solving real operational
• problems, not ju