Data Scientist

Code for Good; Eindhoven; On-site; EUR 39,000 - 56,000; Full time

Benefits offered by this job

Real ownership of platform and tech

Open culture with fast action

Salary €3.500 - €5.000+ per month (var

Growth opportunities

Center of Eindhoven

Job summary

Code for Good in Eindhoven is seeking a Data Scientist to turn raw, real-world data into validated models across images, video, sensor data, and text. You’ll own problems from initial exploration through to a deployable solution, applying robust evaluation and principled experiments.

In this role you’ll move between structured data and unstructured text, selecting the right technique rather than chasing trends. Strong Python, CV/ml experience, and clear communication are essential.

Qualifications

• A few years applying data science and machine learning to real-world problems, ideally beyond academic or research settings.
• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field, or equivalent practical experience
• Strong foundation in statistics and machine learning, with good judgement about which approach fits which problem
• Hands-on experience with computer vision and common deep learning frameworks (e.g. PyTorch, TensorFlow)
• Solid Python skills for data analysis, experimentation and model development
• Experience designing experiments and evaluation methodology, and validating results rigorously
• Comfortable with version control and reproducible experiment workflows
• Able to manage your own priorities across multiple problems, and work independently once a problem is scoped
• Strong communication skills: comfortable explaining technical findings to non-technical stakeholders
• A pragmatic, curious mindset: you care about solving the actual problem, not just optimising a metric

Responsibilities

• Frame open-ended business or client problems as data science problems, and scope an approach that fits the data and the goal
• Build computer vision models for tasks such as detection, classification, segmentation or tracking, and apply comparable rigor to other data types as the problem requires
• Explore and clean data, engineer features, and make deliberate choices about data quality and labeling
• Design sound experiments: define metrics, build evaluation methodology, and validate results against real data rather than assumptions
• Iterate on models based on findings, and know when a simpler, more robust approach beats a more sophisticated one
• Collaborate with engineers, product owners and domain experts to get models working inside a real system, not just a notebook
• Keep experiments reproducible and your work well documented, so others can pick it up, review it, or build on it
• Stay on top of new techniques and tools, and judge honestly whether they're worth adopting for the problem at hand
• Communicate findings, trade-offs and recommendations clearly to both technical and non-technical audiences

Skills

Data science

Machine learning

Statistics

Python

Experiment design

Reproducible workflows

Communication

Independent work

Problem solving

Data visualization

Education

Bachelor's or Master's in Computer Science/Data Science/Statistics/Applied Math

Tools

PyTorch

TensorFlow

Job description

At Code for Good, we connect data, people and AI to help organisations work smarter, faster and more sustainably. We don't do experiments, we deliver measurable return. Technology is the means, not the goal.

Our team designs and builds the Code for Good Platform, a system that turns raw data into real-world impact across six areas of intelligence: Vision, Document, Knowledge, Internal, External and Numbers. With Vision we turn camera feeds into usable data for inspection, sorting and quality control. Document structures information from paperwork and unstructured files, and Knowledge makes an organisation's collective know-how searchable and usable.

Where a standard solution isn't enough, we run innovation tracks: custom development built together with the client and aimed at direct impact. We work across manufacturing, construction and infra, transport and logistics, food and agri, circular resources, and government and defence.

The future of work, as we see it, runs on augmented intelligence: people and technology reinforcing each other rather than one replacing the other.

The Role

We're looking for a Data Scientist to help us turn raw, real-world data into models that solve real problems. You'll work across different types of data — images and video, sensor and numerical data, and text — and take ownership of a problem from first exploration through to a validated solution.

Computer vision is a core part of the work: detection, classification, segmentation and tracking on real-world visual data. Beyond that, you'll move between structured data, unstructured text, and everything in between, choosing the right technique for the problem rather than defaulting to the familiar one.

You'll define the problem together with stakeholders, explore the data, design experiments, and build models you can defend with sound evaluation. Strong intuition for when a simple approach beats a complex one, and the rigor to prove it, matter more to us than chasing the latest technique for its own sake.

What you will do

• Frame open-ended business or client problems as data science problems, and scope an approach that fits the data and the goal
• Build computer vision models for tasks such as detection, classification, segmentation or tracking, and apply comparable rigor to other data types as the problem requires
• Explore and clean data, engineer features, and make deliberate choices about data quality and labeling
• Design sound experiments: define metrics, build evaluation methodology, and validate results against real data rather than assumptions
• Iterate on models based on findings, and know when a simpler, more robust approach beats a more sophisticated one
• Collaborate with engineers, product owners and domain experts to get models working inside a real system, not just a notebook
• Keep experiments reproducible and your work well documented, so others can pick it up, review it, or build on it
• Stay on top of new techniques and tools, and judge honestly whether they're worth adopting for the problem at hand
• Communicate findings, trade-offs and recommendations clearly to both technical and non-technical audiences

What you need to succeed

• A few years applying data science and machine learning to real-world problems, ideally beyond academic or research settings
• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field, or equivalent practical experience
• Strong foundation in statistics and machine learning, with good judgement about which approach fits which problem
• Hands-on experience with computer vision and common deep learning frameworks (e.g. PyTorch, TensorFlow)
• Solid Python skills for data analysis, experimentation and model development
• Experience designing experiments and evaluation methodology, and validating results rigorously
• Comfortable with version control and reproducible experiment workflows
• Able to manage your own priorities across multiple problems, and work independently once a problem is scoped
• Strong communication skills: comfortable explaining technical findings to non-technical stakeholders
• A pragmatic, curious mindset: you care about solving the actual problem, not just optimising a metric

Real depth in at least one of:

• Computer vision: object detection, classification, segmentation, tracking, or working with non-standard sensors
• Applied statistics and modeling: experimental design, evaluation methodology, or structured/tabular and time-series data
• Language and knowledge systems: NLP, retrieval, document structuring, or LLM-based approaches

Nice to have

• Experience taking models into production: packaging, deployment, monitoring and iterating based on real-world performance
• Familiarity with MLOps tooling: inference servers, experiment tracking, or CI/CD for ML
• Exposure to edge hardware and running inference outside the cloud
• Experience supervising interns or junior team members

What We Offer

• Real ownership and freedom to shape our platform and technology
• An open culture where your ideas turn into action quickly
• Salary €3.500 - €5.000+ depending on experience and impact
• Growth opportunities as we build and scale together
• A friendly work environment in the center of Eindhoven

Additional Information

• Office-first culture, based in the center of Eindhoven
• Small team with direct impact on product and technology decisions
• Flat hierarchy with short lines of communication
• We are not our first startup and have experience building and scaling technology businesses
• Full-time role (40 hours per week)
• Learning and development budget available, discussed together based on your goals and ambitions

Please note

• This is an office-first position in Eindhoven
• Applicants must already live in the Netherlands within commuting distance of the office
• We cannot offer visa sponsorship at this time