You have an advanced degree in Engineering, Computer Science, Mathematics, Statistics, Physics or related area;
Strong communication skills in Portuguese and English, both spoken and written;
Experience working on data analysis related functions;
Experience on automotive industry is a strong differential;
Programming skills in Python, R, SQL, DAX;
Experience with large real-world datasets;
Experience with Machine Learning Methods: Unsupervised, supervised and reinforcement learning methods;
Experience with Artificial Intelligence is a plus;
Data access and extraction (ETL) knowledge from Data Warehousing (e.g., IBM) and Data Lakes (e.g., Azure) as well as coding versioning management tools (e.g., Bitbucket, GIT);
Analytics tools familiarity such as Pandas, Numpy, Scikit-learn, Spark, Hadoop, SPSS, Pyodbc and others.
Data mining and analysis, which refers to the application of statistics in the form of exploratory data analysis and machine learning and IA models to reveal patterns and trends in data from existing data sources;
Maintain databases in support of high volume, complex data transactions for specific services or groups of services;
Transform data into a useful format for analysis, managing the source, structure, quality, storage, and accessibility of the data so that it can be queried and analyzed by other analysts;
Being able to present data in a visually appealing way has become part of almost every business analyst and data scientist role.