Grow with us

About this opportunity:

Our Exciting Opportunity We are seeking a technically curious Data Science Intern to join our applied analytics team. You will collaborate with experienced data scientists and engineers to transform data into actionable insights and help deliver reproducible, well-tested analyses. This internship is hands-on: you will contribute to model development, experiment design, and end-to-end workflows while learning production-aware practices such as version control, containerization, and basic deployment patterns.

What you will do:

Translate business problems into measurable data questions and define evaluation criteria (metrics, baselines).

Prepare and engineer features from structured and unstructured sources; write clear, reproducible data pipelines and SQL queries.

Implement, train, and evaluate models (regression, classification, clustering, simple neural networks) with attention to cross-validation, hyperparameter tuning, and performance monitoring.

Develop notebooks and modular Python code (with unit tests and documentation)



and help package work for reproducibility (Git, virtual environments, Docker basics).

Produce clear visualizations and model summaries to communicate results and limitations to stakeholders.

Collaborate in code reviews, experiment tracking, and model validation; learn essentials of MLOps (model versioning, basic deployment concepts).

To be successful in the role you should have: Education & Knowledge:

Currently enrolled in or recently graduated from Data Science, Computer Science, Statistics, Mathematics, Engineering, or related field.

Solid grounding in statistics, basic probability, and core machine learning concepts (bias/variance, regularization, evaluation metrics).

Skills & Tools:

Proficient in Python and familiar with common libraries (pandas, numpy). Strong emphasis on writing modular, readable code.

Experience with Jupyter notebooks and at least one ML library (scikit-learn required; e

📌 Data Scientist Intern (Madrid)
🏢 Ericsson
📍 Madrid