Data Scientist (ML & Statistical Modelling)

Pacmed; Amsterdam; On-site; EUR 70,000 - 100,000; Full time

Benefits offered by this job

Stock Appreciation Rights program

Development Day

Regular social events

Pension contribution of 6%

Birth and maternity leave

Flexible working arrangements

25 paid holidays per year

Option to buy 5 extra holidays

Sabbatical after permanent contract

Lunch provided daily at the office

ClassPass and OpenUp subscription

Public holiday swap option

Company laptop, phone allowance and 홈오

Job summary

Pacmed is seeking a Data Scientist to strengthen our core model development capacity, focusing on machine learning and statistical modelling using large‑scale medical data. You will develop, validate and deploy models to improve patient flow and capacity management across Dutch hospitals.

You will work through the full ML lifecycle, collaborate with a multidisciplinary team, and help build scalable, reliable solutions while meeting medical and information-security regulations.

Qualifications

• Master's degree or equivalent in Data Science, CS, Statistics, or similar.
• Strong proficiency in Python with common libraries (scikit‑learn, pandas/polars, numpy).
• Solid knowledge of the ML lifecycle from data exploration to 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). Visa sponsorship is not available.

Responsibilities

• Develop and deploy ML models trained on large-scale medical data, improving predictive performance, calibration, and robustness.
• Contribute to statistical modelling for capacity management, combining and extending prediction models into unit- and hospital-level insights.
• Involve in all stages of the ML process for new products, from problem definition through monitoring and reporting.
• Dive into heterogeneous healthcare datasets to improve data quality and model reliability, building scalable solutions.
• Write professional, 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 responsibly to assist in work.
• Participate in validation and verification activities per latest medical and information security regulations.
• Be present in the office a couple of days per week in a hybrid setup.

Skills

Python

ML lifecycle

Data analysis

Problem solving

Team collaboration

English proficiency

Education

Master's degree in Data Science or related

Tools

scikit-learn

pandas/polars

numpy

PySpark

FastAPI

SQL

Docker

VueJS

TypeScript

Job description

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.

Why Pacmed is a great place to work

• 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!

What would be expected of you

• 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.

Requirements

• 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.

Working at Pacmed

The perks our team loves

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

Flexible working arrangements in working hours and working from abroad

…but also:

25 paid holidays per year based on full time employment

The option to buy 5 extra holidays based on full time employment

Possibility to take a 3‑months sabbatical once employed with a permanent contract

Lunch provided daily at the office, with plenty of vegetarian and vegan options

A ClassPass and OpenUp subscription

Option to customize public holidays: swap some standard public holidays for alternative days to accommodate personal or religious observances

Company laptop, phone allowance and home office equipment provided

Our Tech Stack

Our software is written in Python and Javascript (Typescript), with Azure as our cloud provider. On the data science side, you will work mostly in Python: we process clinical data with Pandas, Polars, and (Py)Spark, and we train and evaluate our models with scikit‑learn and related libraries (e.g., scikit‑survival, LightGBM). Interpretability and explainability are central to how we build: our predictions only create value when users understand, trust and use them. Around all this sits our product stack — FastAPI, SQL, VueJS, Docker — which you will encounter when your work finds its way into the product. Of course, no single person knows and uses all these tools! So don't worry if you don't know some of them. And if you are curious about any new tool, you will definitely have the chance to pick them up and learn on the job.

At the same time, we are always eager to add beneficial new technologies to our stack. If you want to contribute your expertise with a specific tool that you love, we have a Tech Funnel process to evaluate and possibly adopt anything that might be interesting and beneficial to the team and/or our product.

Growing at Pacmed

At Pacmed we are fully committed to help you grow in the direction that you envision for yourself. Together with your manager, you will craft a development path to guide you in the process. Every quarter you will review your individual growth goals, both with your manager and your team lead, to make sure that you are working on the right things and achieving the goals you have set for yourself.

As a successful Data Scientist, here's an example of what the next 5 years at Pacmed could look like. Of course, this is just a hypothetical path: everyone's professional growth looks different, and every step of the way is highly dependent on a number of factors, including but not limited to one's own performance, but also the needs of the team and the availability of positions.

In the short term (1-3 years) you could grow into a Senior position, in which you will own big(ger) parts of our data science work; design and execute complex analyses and experiments; scope and drive medium- and long-term projects; contribute to the strategic vision of the product and tech team; work closely with team leads and product managers to plan work and resources.

In the longer term (3-5 years), you would decide to follow either the Manager or Individual Contributor track. As a lead/manager, you would start leading teams and managing direct reports, contributing to the company and product strategy, helping to draft goals, manage resources, hiring, etc. As an individual contributor, you would be able to focus on leading the clinical and data science strategy of the team, being responsible for large(r) analytical and product decisions, and for delivering data science work of the highest quality.