• Established and manage the organization's data science and AI group, leveraging Big Data sets and cutting-edge machine/deep learning algorithms to directly impact the organization's bottom line• Lead innovative generative AI projects, revolutionizing claims processing and knowledge management systems within the insurance sector• Provide leadership in emerging quantitative fields, particularly NLP and generative AI applications in insurance• Develop and communicate goals, strategies, project plans, and KPIs while maintaining a collaborative work environment• Offer technical mentorship to data scientists and algorithm engineers, guiding technical thinking and fostering innovation• Collaborate effectively with all levels of staff and management to drive AI-powered transformation across the organization• Maintain a hands-on approach, dedicating 20% of role to direct involvement in projects• Leverage deep understanding of insurance business, risk assessment, and emerging AI technologies to drive strategic initiatives

Responsible on research, design, development and deployment of algorithms and models for malware detection on network flows using Deep learning and other Machine learning techniques. Primary fields of research are: 1. Anomaly detection - using Host profiling methods, time series forecasting, and outlier detection 2. Incident classification - using cluster analysis 3. Domain reputation - using diverse of supervised techniques 4. DGA detection - using Deep learning RNN / LSTM Working end zone on large data sets with all popular technologies: Python, pandas, pyspark, ELK, etc... In parallel, as part of security team every day tasks, I research malicious incidents on CATO customer accounts

Development of end-to-end projects for predict call centers trouble tickets outcomes and computer networking faults, using a variety of ML and Big data technologies. Starting from ingest the data from multiple structured and unstructured sources, data pre processing and relevant features detection, decomposition and extraction, build and evaluate models, and assessment of model accuracy over timeResponsible of design and development of many short proof-of-concept projects for AT&T cyber security and CSO, Examples: Automatic process of IPS signatures, Wi-Fi rogue devices detection. Etc..End zone with all relevant tools: python pandas/sklearn, pyspark, ELK…

Lead research and development of advanced machine learning algorithms for company security products: Detection / Forensics of Compromised / Phishing sites for Cyren CWS (HTTP proxy) reputation service – Based on user transaction graph building and clusteringAutomatic generation of C&C HTTP based signatures, Based on traffic data from Cyren Sandbox service, and Cyren CWS dataSome research on Spear phishing filed for CES (Cyren email security)

• Responsible for R&D of projects in network Security and Cyber Analytics. • Manage a department of 12 Academic and programmers.• Manage Big Data Hadoop project for Cyber analytics. • Analysis, design and management of technology tender processes.• Implementation and Integration of commercial InfoSec solutions (such as FW, IPS, NAC, SIEM, PKI, and Access Control Systems).

Managed the information security in several units of the intelligence corps, responsible for security solutions, methodologies and practices.Lead a team of 7 developers and project managers. The team manages security projects and the development of proprietary security mechanisms. A formal member of the intelligence corps security committee.