English
Svenska
Dansk
Dutch
Français
Norsk
Suomi
Giovanna A.
Data Scientist
Giovanna is an experienced Data Scientist with a strong background in credit scoring and real-time fraud detection, specializing in applying machine learning models to large datasets.
Her notable achievements include the deployment of an entire online real-time fraud scoring workflow, which enabled the analysis of hundreds of thousands of payments using heuristics and machine learning models. Giovanna possesses deep expertise in machine learning algorithms, statistical analysis, and data visualization techniques, with a proven track record of successfully implementing models to solve complex business problems.
Outside of her professional pursuits, Giovanna is passionate about reading, singing, and dancing, and she maintains a strong curiosity for learning new things.
Hauptkompetenz
- Data Analytics 7 Jahre
- Data Science 7 Jahre
- Machine Learning 7 Jahre
Andere Fähigkeiten
- Pandas 2 Jahre
- Git 2 Jahre
- Hadoop 1 Jahre
Ausgewählte Erfahrung
Beschäftigung
Data Scientist
Vizu Labs - 1 jahr 6 monate
Attribute detection in images for fashion retail using machine learning algorithms
- Technologies: AWS S3, Amazon SageMaker, AWS EC2, Google Cloud Platform, GCP Storage, Cloud run, Cloud functions, Docker, TensorFlow, fast API
Technologien:
- Technologien:
- Data Analytics
- Data Science
Machine Learning
AWS S3
Risk and Fraud Manager
Pagseguro - 10 monate
Managed a team of twelve professionals, responsible for the fraud prevention strategy, models and study environment administration for banking and e-commerce transactions:
- Weekly Fraud Committee presentations with the main strategies and results;
- Daily monitoring of fraud KPIs;
- Daily monitoring and studying of new fraud heuristics performance;
- Build, Deploy and maintain Machine Learning Models for post-anomaly detection for the temporary detention of money in case of fraud;
- Build, Deploy and maintain machine learning predictive models for real-time fraud risk scoring;
- Maintain a useful Data Science environment as well as a Data Lake on AWS for studies and predictive model building;
- Daily monitoring of attacks in order to create rules to stop fraud in E-commerce, Face-to-Face Payments and Pagbank transactions.
Technologien:
- Technologien:
- Data Analytics
- Data Science
-
Machine Learning
Python
AWS
-
AWS S3
Lead Data Scientist
Pagseguro - 2 jahre 6 monate
Led a team of five Data (Scientist/Engineers) Analysts that:
- Rebuilt the "Online Game Payments Fraud Scoring", reducing losses related to frauds on a average of 30%;
- Built a predictive model for the new Payment API, marketed to online marketplaces;
- Built and deploy predictive models using various machine-learning tools for post anomaly detection for the temporary detention of money in case of fraud, recovering over 50% of a fraud chargeback;
- Test new data sources, measuring the costs (in case of being external) and benefits of new information;
- Study and create new features to improve real-time fraud scoring;
- Set up and maintain a Data Science environment and a Data Lake on AWS.
Technologien:
- Technologien:
- Data Analytics
- Data Science
-
Machine Learning
-
Python
SQL
-
AWS
-
AWS S3
Data Scientist
Pagseguro - 3 jahre
- Migrate the entire Payment Workflow to a new environment, obeying its limitations and maintaining the previous results;
- Build and deploy predictive models using various machine learning tools for real-time fraud prevention on e-commerce payments;
- Design models to detect anomaly in face-to-face payments, allowing retention and recovery of chargebacks related to crimes;
- Explain complex modelling in an understandable and relatable way;
- A/B Tests to create heuristics to prevent new frauds;
- Credit Scoring Modeling for P2P Loans.
Technologien:
- Technologien:
- Data Analytics
- Data Science
-
Machine Learning
-
Python
-
AWS
Ausbildung
BSc.Statistics
Universidade de São Paulo · 2011 - 2014
Finden Sie Ihren nächsten Entwickler innerhalb von Tagen, nicht Monaten
In einem kurzen 25-minütigen Gespräch würden wir gerne:
- Auf Ihren Bedarf bezüglich des Recruitments von Software-Entwicklern eingehen
- Unseren Prozess vorstellen und somit wie wir Sie mit talentierten und geprüften Kandidaten aus unserem Netzwerk zusammenbringen können
- Die nächsten Schritte besprechen, um den richtigen Kandidaten zu finden - oft in weniger als einer Woche