Staff Data Scientist, Harvest Forecasting (Amsterdam)”

Source.ag; Amsterdam; Hybrid; EUR 120,000 - 150,000; Full time

Benefits offered by this job

Hybrid work

Meals provided on office days

Pension contribution

Well-being support

Equipment: 16" MacBook Pro

Commuting travel allowance

Learning budget: €1,000 annually

Home setup budget: €550

Connectivity: €50/month for WiFi/phone

Flexible holiday policy and minimum 25

Quarterly company events

Job summary

Source.ag in Amsterdam is seeking a Staff Data Scientist to own harvest forecast accuracy and to build hybrid models that combine crop physiology with climate data. You’ll work with data scientists, crop scientists and growers to deliver production-ready forecasts.

You will design robust evaluation backbones, conduct backtests, calibrate uncertainty, and ensure models perform reliably in production while mentoring peers and advancing the team’s technical standards.

Qualifications

• Around 10 years of hands‑on modeling or forecasting in real systems.
• Forecasts that were not trusted and turned into business decisions.
• Models that broke with changes in the environment and were fixed.
• Deep expertise in time series and probabilistic forecasting.
• Validation tying error analysis to business impact and drift monitoring.
• Production‑grade Python and solid engineering habits (Git, testing, CI/CD, Databricks, AWS).
• MSc or PhD and first-principles reasoning.
• AI‑native work with AI agents and LLM tools.
• Collaboration with teams and clear communication with stakeholders.

Responsibilities

• Own the accuracy of harvest forecasts for tomato, pepper and cucumber, especially during unusual weeks.
• Decide which problem to fix first, including input data, plant sampling, or growers’ planning.
• Design and build hybrid models that combine crop physiology and greenhouse climate with statistical methods.
• Build evaluation backbone: backtests on past seasons, strong baselines, uncertainty calibration, production monitoring.
• Ship models to production with engineers and maintain their behavior in production.
• Raise the bar of the data science team through review, challenge, and mentoring.

Skills

Time series forecasting

Probabilistic forecasting

Bayesian models

Hierarchical models

Gradient boosting

Deep learning for sequences

Uncertainty quantification

Production-grade Python

Git

Testing

CI/CD

Databricks

AWS

Education

MSc or PhD in a quantitative field

Tools

Python (pandas/polars)

PyTorch or JAX

PyMC or similar

Scikit-learn

Git

CI/CD tooling

Databricks

AWS

Job description

Source.ag in Amsterdam is seeking a Staff Data Scientist to own harvest forecast accuracy and to build hybrid models that combine crop physiology with climate data. You’ll work with data scientists, crop scientists and growers to deliver production-ready forecasts.

You will design robust evaluation backbones, conduct backtests, calibrate uncertainty, and ensure models perform reliably in production while mentoring peers and advancing the team’s technical standards.