ML Intern: Ensure Explainable AI for Marketing Budgets

Nexoya Ltd.; Zürich; On-site; CHF 45,000 - 70,000; Full time

Job summary

Nexoya Ltd. in Zürich, Switzerland, is seeking an ML Intern to support automated budget optimization and simulations across ad channels.

You will monitor pipeline health, check prediction quality, and collaborate with ML engineers and Customer Success to ensure outputs are correct, explainable and timely. You will implement plausibility checks, investigate anomalies, automate checks with Python, and help maintain dashboards and runbooks.

Qualifications

• Master's degree in a relevant field with strong data science foundations.
• Solid Python, pandas and NumPy skills for data manipulation and modeling.
• Experience with SQL and basic statistics for evaluating models.
• Understanding of regression, model evaluation and overfitting concepts.
• Ability to explain technical findings to non-experts and document work clearly.
• Fluent English, written and spoken; German or Italian is a plus.

Responsibilities

• Monitor automation and assure result quality before reaching customers.
• Investigate failed or unexpected runs and diagnose root causes.
• Define plausibility checks for optimization and simulation results.
• Ensure results are consistent and explainable to customers and account managers.
• Compare optimized and simulated outcomes with realized performance and document deviations.
• Monitor input data for gaps and tracking changes affecting quality.
• Track model fit and prediction accuracy per portfolio and flag degradation.
• Automate workflow with Python scripts and build dashboards for status and health.

Skills

Python

pandas

NumPy

SQL

statistics

ML concepts

communication

English

Education

Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering or related field

Tools

Git

Docker

Cloud environments

Data pipelines

Job description

Nexoya Ltd. in Zürich, Switzerland, is seeking an ML Intern to support automated budget optimization and simulations across ad channels.

You will monitor pipeline health, check prediction quality, and collaborate with ML engineers and Customer Success to ensure outputs are correct, explainable and timely. You will implement plausibility checks, investigate anomalies, automate checks with Python, and help maintain dashboards and runbooks.