Data Scientist

Qabird; Delft; On-site; EUR 70,000 - 110,000; Full time

Job summary

Luo seeks a Data Scientist to advance detection models used in pharmaceutical quality inspections. You will build, adapt, and evaluate models in real time on hardware, focusing on image data and industrial datasets.

Collaborate with engineers and domain experts to annotate data, run experiments, and communicate findings clearly to non-technical stakeholders. This role offers hands-on ownership and real impact.

Qualifications

• Strong ML Foundation: You have solid experience with Python and machine learning frameworks such as PyTorch or TensorFlow.
• Data Analysis: You have a strong focus on analyzing image data, understanding patterns, and extracting meaningful insights to improve model performance. Experience with medical or industrial datasets is a plus.
• Hands-On Experience: You are comfortable owning the full pipeline, including data collection, annotation, and running experiments independently when needed.
• Analytical and communicative: You can explain complex findings clearly to non-technical people. You understand how to tailor your message to your audience.
• Eye for quality: You recognize that in the pharmaceutical industry accuracy is critical and understand the real-world impact of your models, especially when it comes to patient safety.
• Direct and transparent: You communicate openly about challenges. If a model underperforms or data is insufficient, you raise your concerns early so we can solve them together.

Responsibilities

• Staying up to date: Following the latest developments in detection models and AI, assessing what’s relevant for our custom models, and translating this into concrete research actions.
• Building and improving detection models: Adapting existing models to new clients, improving detection, and qualifying models’ performance offline.
• Orchestrating data strategy: Managing and executing dataset annotation for model training and defining which data needs to be available to build and improve the best detection models.

Skills

Python

PyTorch

TensorFlow

Data analysis

Model evaluation

Independent pipeline work

Job description

Now Hiring: Data Scientist in high-tech scale-up At Luo, we build machines that automate quality inspections of medicine. In many pharmaceutical environments, people still spend hours manually checking products for particles, cosmetic defects, and packaging integrity issues. It’s tedious and humans make mistakes. We build machines that do this job more accurately, faster, and consistently. The brains of our machines are the detection models: algorithms that decide in real time whether a product passes inspection. We’ve proven the technology works. Now we’re scaling and that means more clients, more applications, higher accuracy. For that, we need someone who builds, improves, and pushes these models to the next level.

What you’ll work on

• Staying up to date: Following the latest developments in detection models and AI, assessing what’s relevant for our custom models, and translating this into concrete research actions.
• Building and improving detection models: Adapting existing models to new clients, improving detection, and qualifying models’ performance offline.
• Orchestrating data strategy: Managing and executing dataset annotation for model training and defining which data needs to be available to build and improve the best detection models.

What we are looking for

• Strong ML Foundation: You have solid experience with Python and machine learning frameworks such as PyTorch or TensorFlow.
• Data Analysis: You have a strong focus on analyzing image data, understanding patterns, and extracting meaningful insights to improve model performance. Experience with medical or industrial datasets is a plus.
• Hands-On Experience: You are comfortable owning the full pipeline, including data collection, annotation, and running experiments independently when needed.
• Analytical and communicative: You can explain complex findings clearly to non-technical people. You understand how to tailor your message to your audience.
• Eye for quality: You recognize that in the pharmaceutical industry accuracy is critical and understand the real-world impact of your models, especially when it comes to patient safety.
• Direct and transparent: You communicate openly about challenges. If a model underperforms or data is insufficient, you raise your concerns early so we can solve them together.

What it’s like to work here

• Real impact: Your models run in real machines at real client sites. When you improve something, you directly see the effect!
• Flat structure, short lines. Good idea? Go for it.
• Interesting challenges: Detection problems in the pharmaceutical industry are complex and demanding. You’ll work at the edge of technology, where quality standards are high.
• A solid team: You work alongside engineers, operational, and commercial teams who all share the same goal. Cooperation and teamwork are key to building and delivering machines that actually work.