Data Analyst Intern

at  Webfleet Solutions Sales BV

At Bridgestone Mobility Solutions we are looking for an enthusiastic, highly motivated and results oriented Intern Data Analyst in Barcelona to join our Marketing Analytics team. As an Intern Data Analyst you will work on real products, data-based insights, leveraging and exploring hundreds of million data points, such as customer characteristics, behaviour, fleet usage, fleet characteristics and usage data. You will be part of our core business unit, Webfleet Solutions Europe, as part of the Marketing Analytics team to help taking business decisions based on data. You will be a member of a cross functional team, including Data Analysts, Product managers, Marketing analysts and Data Scientists. You will collaborate and be supported by an experienced and strong team, taking the steps to the new AI era.

• Strong problem-solving skills, analytic mind, achievement orientation, sense of quality, flexible thinking. You are a self-driven team player with a passion for results.
• You had exposure visualizing and presenting data utilizing Power BI (DAX formulas), Tableau, matplotlib, or Plotly.
• Mandatory to be able to make a 6-to-12-month agreement with the university (from a Masters, Doctorate, Undergraduate or Graduate degree).
• Analytical, mathematical, and statistical mindset.
• Keen eye for detail and passion for data/reporting integrity.
• Determination to propose and implement changes based on reasoned assessments.
• Fluency in English (verbal and written) is critical.
• Knowledge of Salesforce (company CRM) is a plus.
• Sociable person who likes to work in a team.
• Dependable and takes ownership when faced with challenges.
• It will be also nice to have
• Academical experience in building statistical models, manipulating data sets
• You can utilize different kinds of data sources, such as relational databases via SQL, non-relational databases, and different types of web interface providing structured and unstructured data in json, xml, or other common data formats.
• You have knowledge and experience with Python or other object-oriented programming language.
• You have deep understanding and already applied some unsupervised-learning techniques, such as k-mean, Gaussian mixture models, DBSCAN, self-organized maps, or autoencoders, as well as in standard supervised learning techniques like regression, random forests, naive Bayes. Ideally, you have designed deep learning models in Keras or PyTorch.
• Experience with the following frameworks, standards, and software categories: Spark, Azure, or similar.
• Some experience in a similar positio