Pessoa Engenheira de Inteligência Antifraude Pleno
J
JobgetherFintech Security
BrazilFull-TimeMiddle
Salary not disclosed
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Job Details
- Required Skills
- AWSDockerPythonSQLCloud ComputingData AnalysisGitMachine Learning
Requirements
- Bachelor’s degree in Statistics, Computer Science, Engineering, or related fields.
- Previous experience working as a Data Scientist or in a similar data-focused engineering role.
- Strong programming skills in Python for data analysis, automation, and application development.
- Knowledge of SQL and experience working with structured data.
- Experience with Git or other code version management tools.
- Strong understanding of statistical analysis, modeling techniques, and data-driven decision-making.
- Familiarity with cloud computing concepts and platforms.
- Strong analytical mindset, problem-solving skills, and ability to collaborate with cross-functional teams.
- Experience with fraud prevention, financial services, banking, payment solutions, or fintech environments is a strong advantage.
- Knowledge of Clean Code, Clean Architecture, unit testing practices, and web application deployment is desirable.
- Experience with AWS and Docker is considered a plus.
Responsibilities
- Perform exploratory data analysis to identify patterns, trends, and insights that support antifraud strategies and decision-making.
- Design, implement, test, and optimize antifraud rules based on data analysis and business requirements.
- Monitor the performance of fraud detection rules, making preventive and corrective adjustments to improve effectiveness.
- Develop, test, and deploy systems and APIs with a focus on code quality, readability, scalability, and performance.
- Build and enhance machine learning models focused on fraud detection and prevention.
- Contribute to improvements in team processes, workflows, tools, and operational efficiency.
- Collaborate closely with different teams to ensure consistency, integration, and continuous improvement of antifraud initiatives.
- Apply statistical analysis techniques to support more accurate fraud detection strategies.
- Participate in technical discussions and contribute to the evolution of security and data-driven solutions.
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