The Data Scientist role today
This guide draws on 933 Data Scientist postings from 518 companies, published from March to September 2026.
In 45% of Data Scientist postings, building or applying AI is the job itself.
Machine Learning appears in 67% of Data Scientist postings, and MLOps in 32%.
Automation exposure averages 36 out of 100 across these postings, which is moderate: parts of the routine work can be automated, which makes AI skills more valuable in the role.
Senior positions make up 32% of postings, entry-level 32%. The most common way of working is hybrid, in 54% of postings.
Common skill gaps
The AI skills our analysis of Data Scientist job descriptions most often flags as a gap, with the share of postings where each one comes up.
- MLOps45%
- Prompt Engineering34%
- AI Ethics34%
- LLM Fine Tuning25%
- Feature Engineering18%
- Model Deployment17%
Data Scientist salary
Pay comes only from postings that quote it: 55 of the 933 Data Scientist postings. Each country uses the pay period its employers quote most.
Netherlands
based on 55 postings quoting pay per month€5,400
median per month
The middle half of advertised salaries, with the line at the median.
Essential Data Scientist skills
The skills employers ask for in Data Scientist job descriptions, from the most requested down.
Core skills
- Python
- Machine Learning
- SQL
Often requested
- MLOps
- Data Visualization
- Statistical Modeling
Also valued
- Generative AI
- Statistics
- PyTorch
- Deep Learning
AI skills to learn next
The AI skills employers most often want to add to this role, beyond the ones above.
- Cloud ML Platforms
How the Data Scientist role is evolving
The directions employers are taking this role as they adopt AI, with the skills and responsibilities each one adds.
Most common direction
Toward data & machine learning
Typical focus
AI & machine learning and AI model evaluation
New responsibilities
- Deploy and monitor machine learning models in production environments
- Monitor model performance and retrain as needed
- Deploy machine learning models to production using MLOps pipelines
- Collaborate with engineering to integrate models into production systems
Other directions
Toward AI product
Typical focus
AI product innovation, AI product strategy and AI product analytics
Skills to add
- AI Product Management
- AI Strategy
- Stakeholder Management
- AI Product Strategy
- AI Roadmapping
New responsibilities
- Measure and communicate the business impact of AI initiatives
- Define and prioritize AI use cases aligned with business goals
- Define and prioritize AI features for internal data products
- Evaluate and prioritize AI use cases based on business impact and feasibility
Toward AI engineering
Typical focus
Generative AI, AI systems and Agentic AI
Skills to add
- Vector Databases
- LLM Ops
New responsibilities
- Fine-tune and evaluate large language models for domain-specific tasks
- Design and implement retrieval-augmented generation (RAG) pipelines for enterprise applications
- Design and implement scalable ML pipelines for production
- Collaborate with engineering teams to integrate AI solutions into products
Toward AI transformation
Skills to add
- Change Management
- AI Governance
- Stakeholder Engagement
New responsibilities
- Advise clients on AI adoption strategies and roadmap development
- Measure and communicate the business impact of AI initiatives
- Advise senior leadership on AI opportunities and risks
- Develop and execute AI adoption roadmaps in collaboration with business units
Data Scientist FAQ
Will AI replace Data Scientist jobs?
Automation exposure averages 36 out of 100 across these postings, which is moderate: parts of the routine work can be automated, which makes AI skills more valuable in the role. Employers are mostly reshaping the role toward data & machine learning, adding skills such as MLOps and Deep Learning.
What skills do Data Scientist roles require?
The skills employers ask for most are Python, Machine Learning, SQL, MLOps and Data Visualization.
Which AI skills should Data Scientist candidates learn next?
MLOps, Prompt Engineering and LLM Fine Tuning are the AI skills employers most often want to add. The most common skill gaps are MLOps and Prompt Engineering.
How is the Data Scientist role changing?
The most common direction is data & machine learning. Other directions include AI product, AI engineering and AI transformation.
How much do Data Scientist roles pay in the Netherlands?
Advertised salaries typically range from €4,500 to €8,000 per month, with the median around €5,400, based on 55 postings that quote pay per month.
Find your next Data Scientist role
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This guide is built from public job descriptions for Data Scientist roles classified as Core AI or AI-enabled. Skills, automation exposure and career directions are extracted from each job description and compared across the market. Postings are deduplicated, so a job listed on several boards or by several agencies counts once. Salaries are advertised ranges from the Netherlands, taken only from the 55 postings that quote pay. How we collect and deduplicate postings.