We are seeking a highly motivated and analytical Data Scientist Intern to join our Global Audience Insights team in Madrid. As a Data Scientist Intern, you will be responsible for assisting in the development and implementation of data-driven solutions that deliver insights and drive business decisions. You will work alongside experienced data scientists and collaborate with cross-functional teams to analyze complex data sets, build statistical models, develop machine learning algorithms, and create compelling data visualizations.
The internship guide will be the Global Data Science Manager.
Main Responsabilities
- Assist in collecting, processing, and analyzing large and complex data sets to uncover insights and identify trends
- Develop statistical models and machine learning algorithms to predict and optimize business outcomes
- Collaborate with cross-functional teams to identify business problems, define requirements, and develop solutions
- Create visually appealing and informative data visualizations using tools such as Power BI, or matplotlib
- Present findings and recommendationsto internal stakeholders and communicate technical concepts to non-technical audiences
- Continuously monitor and evaluate model performance and refine models as needed
- Stay up-to-date with industry trends and emerging technologies in data science and machine learning (Ex: ChatGPT) • Familiarity with data analysis and data visualization tools such as Python, BigQuery (SQL), PowerBI, etc.
- Basic understanding of statistical concepts and machine learning algorithms
- Strong analytical and problem-solving skills with the ability to work independently and as part of a team
- Excellent communication and presentation skills with the ability to explain complex concepts to both technical and non-technical audiences
Nice to have: - Familiarity with data engineering concepts and tools such as ETL, data pipelines, and data warehousing
- Knowledge in high-level data visualization platforms (power BI).
- Building self-service apps in python
- NLP models
- Experience with cloud computing platforms such as GCP or Azure
- Experience with big data technologies such as Hadoop, Spark, or Hive