Angelo Schranko De Oliveira, Phd Email & Phone Number

San Mateo, California, Us

As a Staff Cybersecurity Data Scientist, I've been working on research, development, and improvement of AppOmni's platform User and Entity Behavioral Analytics (UEBA) features using Big Data, Cloud Computing, and Artificial Intelligence (Machine Learning, Deep Learning, Graph Neural Networks, Deep Generative Models, and Large Language Models (LLMs)) to:1) Identify security trends2) Explore open policy issues3) Monitor all SaaS apps4) Investigate 3rd party apps5) Detect threats and take immediate action6) Route alerts to tools you trust7) Continuously monitor complianceAppOmni is the pioneer of SaaS Security Posture Management enabling customers to achieve secure productivity with their SaaS applications. Our platform gives you visibility and automation to easily secure your SaaS data across all apps.

As the Founder and Chief Nerd Officer (CNO) of csds.tech, I've been working on providing specialized consulting services on building customized solutions for internal threat detection such as malicious users, malware infiltration, and data exfiltration by employing state-of-the-art Artificial Intelligence (AI) algorithms, Data Science, and Data Engineering.

Downers Grove, Il, Us

During the "Cut Score Workshop" SMEs helped to determine and set the passing standard for the certification exam, and created, developed, and reviewed items for the CompTIA PenTest+ exam.

Sao Pablo, Sao Pablo, Br

As a Staff Cybersecurity Data Scientist & Engineer, I've been working with teams of Data Analysts, Data Scientists, and Data Engineers to architect, engineer, develop, integrate, and operationalize intelligent data-driven solutions for insider threat detection, insider data exfiltration detection, and fraud detection. In less than a year, we operationalized and are managing:* A platform for insider threat detection using behavioral data extracted from several security monitoring agents from Storages, Databases, APIs, and from IAM logs and SIEM.As a result, we've been increasing our security posture, making it possible to detect, respond, and prevent previously unknown insider threats.* A platform for insider data exfiltration detection using behavioral graphs built using data extracted from key sensitive internal systems.As a result, we integrated custom insider data exfiltration alerts to SECOps and have been increasing our security posture, making it possible to detect, respond, and prevent previously unknown insider data exfiltration attempts.* A platform for fraud analytics and fraud detection based on behavioral graphs built using data extracted from key sensitive internal systems.As a result, the Internal Accounts Fraud Team has been leveraging the platform to monitor, detect, and understand the behaviors associated with our internal users and establish more effective controls resulting in a greater security posture towards insider fraudsters. ** Tech stack: Google Cloud Platform-based Data Engineering stack - PubSub, Cloud Storage, Dataproc (PySpark), BigQuery, Composer (Apache Airflow), Cloud Functions, Cloud Run. AWS-based Data Engineering stack - Kinesis Streams, Lambda, S3, Glue ETL (PySpark), EventBridge, Redshift. Data Science & Machine Learning stack: scikit-learn, PyTorch Geometric, Optuna, HDBSCAN, Isolation Forest, Random Forest, Transformers, Variational Graph Autoencoders, Graph Attention Neural Networks, GNNExplainer, SHAP.

São Paulo, São Paulo, Br

As a Senior Cybersecurity Data Scientist & Engineer, I've helped XP to build its next-generation real-time security analytics platform. More specifically, I've architected, engineered, developed, and operationalized solutions to help:* The SECOps Team to improve the alert triaging process using Machine Learning and Deep Learning based solutions to learn patterns in the alerts and their correlated events in order to estimate a prioritization ranking representing the probability of a given alert to generate a security incident.As a result, the KPIs Mean Time To Detection (MTTD) and Mean Time To Response (MTTR) decreased in more than 30%. In addition, there was a decrease of more than 35% in false alerts (false positives). This initiative helped the SOC to become more agile and assertive.* The SECOps teams to monitor, detect, identify, and prevent API abuses and abusers such as malicious users, bots, and attackers, using a Deep Learning Graph-based model to learn the patterns associated to normal and anomalous APIs usages.As a result, the Detection Engineering Team was able gain insights on how to implement additional static rules to prevent API abuses and bots from scraping data from Stock Market APIs, and use the models' outputs to enrich the data used for decision making in more complex the detection rules.** Tech stack: Google Cloud Platform-based Data Engineering stack - PubSub, Cloud Storage, Dataproc (PySpark), BigQuery, Composer (Apache Airflow), Cloud Functions, Cloud Run. Data Science & Machine Learning stack: scikit-learn, PyTorch, PyTorch Geometric, Optuna, HDBSCAN, Isolation Forest, XGBoost, Transformers, Graph Neural Networks, GNNExplainer, SHAP.

São Paulo, São Paulo, Br

As Research and Teaching Assistant, I've worked on the research and development of a novel malware detection and classification methods using Data Science, Machine Learning, and Deep Learning. For more information see "Education" and "Publications". In addition, I've lectured on Mathematics for Machine Learning, Machine Learning, Data Science, and Cybersecurity advanced topics. Finally, I've mentored MSc and PhD students, and reviewed research papers.

Sao Paulo, Sp, Br

As Senior Cybersecurity Data Scientist, I've architected, engineered, and operationalized:* Detection models to help the SECOps Team monitor, detect, identify, and prevent abuses in the Protheus ERP REST (and SOAP) APIs, and proprietary binary protocols.As a result, the SECOps Team was able to build whole new threat modeling scenarios and new detection rules, consequently improving the security posture of the main TOTVS product. * A custom guided white-box fuzzer tool to search for vulnerabilities in the Protheus' Application Server AdvPL (Advanced Protheus Language) Interpreter, using binary instrumentation and Reinforcement Learning.As a result several Remote Code Execution vulnerabilities (RCE) where found and fixed before the product releases. The intelligent fuzzer was eventually integrated into the Secure Software Development Life Cycle (SSDLC), which I was responsible for running.Moreover, I was also actively involved in mentoring, training, and supporting software engineers and architects on application security (and insecurity) best practices.In addition, I've initially worked as a Senior Software Engineer in the Protheus Application Platform Squad, helping to develop new business functionalities, optimizations and, of course, fixing bugs!** Tech stack: AWS-based Data Engineering stack - Lambda, Elastic MapReduce (EMR - PySpark), CloudWatch. Data Science & Machine Learning stack: scikit-learn, Keras, Isolation Forest, Random Forest, Reinforcement Learning.

Austin, Texas, Us

As an Official Java Consultant & Trainer at Sun Microsystems (now Oracle) I was responsible to teach the full Java/EE curriculum: Java (Introductory/Intermediate/Advanced), Oriented Object Programming, Web Development (JSP/Servlets/JSF), Enterprise Java Beans (EJB), Java Persistence API (JPA), SOAP Web Services (JAX-WS), REST Web Services (JAX-RS), Enterprise Architecture, and Design Patterns, as well as provide consulting services for Oracle's customers.

São Paulo, Sp, Br

As a Senior Security Researcher at Qiwi, I was mainly responsible for web application penetration testing and backend application penetration testing (SOAP, REST, and binary protocols). I've also performed reverse engineering tasks on ATM products. On top of that, I've supported the development on the design and implementation of secure components.

Stuttgart, Baden-Württemberg, De

As a Senior Software Engineer, I was responsible for running the Secure Software Development Lifecycle (SSDLC) for one of the main US international taxation projects (FATCA) for the Deutsche Bank. My main responsibilities were to design and implement secure-by-design software components, as well as perform security code reviews and security evangelization.

Santiago, Cl

As a Java, C/C++ Software Engineer, I was responsible for the design, development, and integration of several projects (from client-server systems to large Service Oriented Architecture (SOA) integration projects) using Java EE Platform and (mostly) open-source frameworks, tools, runtime environments, and RDBMS. Most of the projects achieved high performance, availability, and scalability by using clustering, load-balancing, pooling, and algorithmic optimizations. Among our main clients were Itaú Bank and Toyota.

Doctor Of Philosophy - Phd (Summa Cum Laude), Informatics

Master Of Science - Ms, Electrical And Electronics Engineering

Bachelor'S Degree, Mathematics