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Responsibilities:
- Assist in extracting, organizing, and analyzing data from different sources for fraud prevention studies.
- Contribute to data preparation and feature engineering for building analytical models.
- Participate in the development, training, validation, and evolution of machine learning models applied to biometrics/liveness, device intelligence, and fraud detection.
Qualifications:
- Degree in Data Science, Statistics, Computer Science, Engineering, or related fields.
- Knowledge of SQL for data extraction, manipulation, and analysis.
- Knowledge of statistical modeling and machine learning.
- Experience with data preparation, analytical exploration, and feature engineering.
What We Expect:
- Curiosity and willingness to learn in a challenging technical environment.
- Responsibility for deliverables and attention to quality.
- Good communication to share learnings, doubts, results, and risks.
- Proactivity to seek knowledge and propose improvements.
Differentials:
- Knowledge of AIRFLOW for pipeline orchestration.
- Experience with OCI.
- Academic or professional experience with fraud, biometrics, liveness, digital identity, or device intelligence.
- Participation in R&D projects, MVPs, POCs, or applied analytical model initiatives.
Serasa Experian
Serasa Experian is the first and largest Datatech in Brazil, a leader in intelligence solutions for risk analysis and opportunities. With 22,000 employees across 32 countries, the company fosters a culture of innovation, inclusion, and well-being, committed to building a better future for people and businesses.