Data Scientist; ML & Statistical Modelling

Do you want to help shape tomorrow’s healthcare with AI? At Pacmed, we combine technology and humanity to keep healthcare accessible and future-proof. We are a growing AI company with solutions already running in multiple hospitals, and we are actively scaling further across the Netherlands.

With our software, we help healthcare professionals make better real‑time decisions, use capacity more efficiently, and ensure smooth patient flows, from the emergency department and ICU to the clinic. Our mission is to help hospitals accelerate their care transformation and digitalization goals, so that every patient receives the right care at the right time.

Does this sound exciting? Then we have the perfect role for you! We are looking for a Data Scientist, focussed on machine learning and statistical modelling, who will strengthen our core model‑development capacity: making our models better, improving their performance and reliability, and building new ones.

• We're a dynamic startup committed to improving healthcare in the Netherlands.

• We're committed to creating an inclusive environment for our team.

• We're a talented bunch dedicated to helping each other grow.

• We foster a culture of kindness and respect.

• We're a team of ambitious and fun‑loving people, with regular team events!

• Develop and deploy machine learning models trained on large‑scale medical data, improving their predictive performance, calibration, and robustness.

• Contribute to statistical modelling for capacity management: combining and extending our prediction models (e.g., admission inflow, discharge, survival models) into unit‑and‑hospital level insights, with attention to uncertainty, calibration, and simulation of patient flow.

• Be involved in all stages of the ML process for new products: from problem definition and algorithmic approach through analysis, pipelining, experimentation, interpretation, certification, and implementation, all the way to post‑market monitoring and reporting.

• Dive into heterogeneous healthcare datasets to improve data quality and model reliability, while building scalable, generic solutions applicable across hospitals.

• Write professional, maintainable, well‑tested code following best practices for medical applications.

• Contribute to R&D and bring new techniques and ideas into the team.

• Use AI tooling wisely and responsibly to assist you in your work.

• Participate in validation and verification activities, according to the latest medical and information security regulations.

• Be present in the office a couple of days per week. We are flexible, and at the same time we love seeing each other regularly and working together in person.

• A Master's degree (or equivalent demonstrated experience) in Data Science, Computer Science, Statistics, or a similar field

• Strong proficiency in Python, including commonly used libraries (e.g., scikit‑learn, pandas/polars, numpy)

• Solid knowledge of the entire machine learning lifecycle — from data exploration and preprocessing to model experimentation, development, validation, deployment, and monitoring

• Energy, curiosity, a product mindset and a learner's mindset; a good team player

• Fluency in written and spoken English

• Eligible to work in the Netherlands (EU). Unfortunately we are not able to sponsor visas at the moment.

At Pacmed, we think there is strength in diversity. Studies show that women and members of underrepresented communities apply for jobs only if they meet 100% of the qualifications. Does this sound like you? If so, Pacmed encourages you to reconsider and apply! Building responsible AI requires diverse perspectives, equitable practices, and integrity every step of the way. This is our commitment.

You’ll get a stake in Pacmed's success through our Stock Appreciation Rights (SAR) program

Development Day once a month – spend 5% of your work time for personal development!

Regular social events, with quarterly outings and yearly off‑site

Sponsored contribution of an equivalent of 6% of your salary to a private pension fund

Extra paid additional birth leave and maternity leave

Flexibl…