Mid Data Scientist

Slashhash; Netherlands; Hybrid; EUR 65,000 - 90,000; Full time

Benefits offered by this job

Health insurance

Job summary

Slashhash is seeking a Mid Data Scientist in the Netherlands to turn complex data into actionable insights and measurable business value. You will build and deploy ML models, perform statistical analysis, data visualization, and contribute to MLOps practices.

We expect 3–5 years of experience, strong Python skills, and a hands-on approach to exploring data, feature engineering, evaluation, and collaboration with stakeholders. The role involves working across data teams to deliver value.

Qualifications

• 3–5 years of data science experience.
• Strong Python skills and hands-on data analysis.
• Experience with ML model development and evaluation.
• Experience with data visualization and BI tools.

Responsibilities

• Conduct exploratory data analysis to identify patterns, trends, and opportunities.
• Build, train, tune, and validate supervised and unsupervised machine learning models.
• Apply statistical methods including hypothesis testing and distribution analysis.
• Develop clear data visualizations using Matplotlib, Seaborn, Plotly, Power BI or Tableau.
• Collaborate with Data teams and stakeholders to deploy analytics solutions and ML models.

Job description

Mid Data Scientist role based in the Netherlands, offered on behalf of a partner company, focused on turning complex data into actionable insights and measurable business value. The position involves building and deploying machine learning models, statistical analysis, data visualization, and MLOps practices, requiring 3–5 years of data science experience and strong Python skills.

Technical (Must-have)

• Python
• NumPy
• pandas
• scikit-learn
• PyTorch
• TensorFlow
• SQL
• MLflow
• Weights & Biases
• Databricks ML
• Matplotlib
• Seaborn
• Plotly
• Power BI
• Tableau

Soft Skills

• Analytical thinking
• Problem-solving
• Communication
• Collaboration
• Ownership
• Adaptability
• Proactive communication

Technical (Nice-to-have)

• Azure ML
• AWS SageMaker
• Google Cloud Vertex AI

Key Responsibilities

• Conduct exploratory data analysis to identify patterns, trends, anomalies, and opportunities.
• Perform feature engineering and prepare high-quality datasets for analytical and machine learning use cases.
• Build, train, tune, and validate supervised and unsupervised machine learning models.
• Apply statistical and probabilistic methods, including hypothesis testing, inference, and distribution analysis.
• Define appropriate evaluation metrics and validation strategies, including cross-validation and overfitting analysis.
• Use experimentation and model management tools such as MLflow, Weights & Biases, or Databricks ML.
• Analyze and query data using SQL.
• Develop clear and informative data visualizations using Matplotlib, Seaborn, Plotly, and BI platforms such as Power BI or Tableau.
• Apply MLOps fundamentals, including model versioning, model registries, and deployment lifecycle practices.
• Work with cloud-based machine learning platforms such as Azure ML, AWS SageMaker, or Google Cloud Vertex AI.
• Communicate analytical findings and technical insights clearly to both technical and non-technical stakeholders.
• Collaborate with Data teams to integrate analytical solutions effectively across projects.
• Take ownership of model quality, reliability, and the overall analytical lifecycle.
• Adapt analytical approaches and models to changing datasets, requirements, and project objectives.
• Proactively identify problems and communicate solutions in a structured, value-oriented manner.

Python, NumPy, pandas, scikit-learn, PyTorch, TensorFlow, SQL, MLflow, Weights & Biases, Databricks ML, Matplotlib, Seaborn, Plotly, Power BI, Tableau, 5 years of relevant experience