Especialista Cientista de Dados - Afirmativa para Mulheres
The DataLab is the research and innovation unit of the Experian group in Latin America, in partnership with Serasa Experian in Brazil. Our goal is to be proactive, anticipating the future, and consultative, identifying opportunities for market evolution through Artificial Intelligence and Machine Learning techniques combined with the use of new data sources. We create advanced innovative solutions that help clients and the market prepare today for more assertive decisions tomorrow. Additionally, we maintain a 360º perspective to exchange with the best globally, considering the whole and producing solutions capable of achieving great scalability.
As a Data Science Specialist, you will play a central role in the team, utilizing your experience and knowledge in Machine Learning, GenAI, programming, data processing, and analysis to technically lead projects alongside engineering and business teams. Your main responsibilities will include proposing and implementing advanced data analyses and Machine Learning models, efficiently handling large volumes of data, collaborating with Data Engineering, Software Engineering, Product, and Business teams to understand needs, suggesting data-driven solutions, and positively influencing project directions. You will also continuously explore new data sources and technical innovations, stay updated with the latest research and advancements in GenAI and Machine Learning, present results and recommendations to stakeholders and executive teams, design roadmaps for data-driven product development in line with business needs, and conduct experiments and tests in an agile manner aiming for conclusive decisions.
We are looking for candidates with a bachelor's degree in Data Science, Statistics, Computer Science, Engineering, Physics, or related fields. Strong knowledge in Python, especially in data manipulation, analysis libraries (e.g., Pandas, Numpy), and Machine Learning frameworks (e.g., scikit-learn, TensorFlow) is essential. Experience in handling large databases, particularly stored in Hadoop environments (HDFS), distributed data processing (PySpark), and SQL language is required. Proficiency in developing and deploying Machine Learning models, with good knowledge in validation, tuning, and monitoring of models, as well as experience in code versioning, is also necessary. The ideal candidate should have the ability to understand and solve business problems in a versatile and agile manner, communicate effectively with peers, partner areas, and executives, including presentations and translating insights into business actions, collaborate and work in a team, engage in continuous learning, possess advanced English skills, and be available for hybrid work (twice a week) in São Paulo/SP (Chácara Santo Antônio).
Desirable qualifications include a master's or doctoral degree in related areas and knowledge and experience with graph processing and complex networks.
Serasa Experian is much more than you imagine. With the purpose of creating a better future by expanding opportunities for people and businesses, in Brazil, we are more than 4,000 people working in various teams and specialties. Here, each knowledge and diversity complement each other, and you can work on what you love most. We are committed to building an inclusive culture and an environment where people can balance their careers with their personal commitments and interests, prioritizing well-being. We are dedicated to being one of the best and most innovative companies to work for in the country, enabling incredible experiences and careers for our people. Our strong people-first approach is externally recognized through various market certifications: we have been awarded by Great Place To Work™ in 24 countries and by the international Top Employers certification, in addition to being recognized as one of the best companies for young professionals and having a 4.6 rating on Glassdoor. Each recognition indicates that we are on the right path, providing an increasingly better work environment for our talents.