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Job DescriptionJob Description
- Design and implement machine learning models for authentication, fraud detection, and cybersecurity threat prediction.
- Develop advanced behavioral analytics solutions to detect anomalies in user authentication and access patterns.
- Collaborate with cybersecurity teams to integrate AI-driven solutions into security platforms and workflows.
- Research and implement cutting-edge techniques in AuthAI , including deep learning for verification and continuous authentication.
- Build and maintain scalable data pipelines for security event monitoring and threat detection.
- Conduct data experiments to assess new authentication methods, biometrics, and risk-based models.
- Interpret and present insights to senior stakeholders to support data-driven decision-making in cybersecurity strategies.
- Ensure all models, methods, and solutions comply with data privacy regulations and organizational security standards.
Requirements
- Strong proficiency in machine learning, deep learning, and data science tools (Python, R, TensorFlow, PyTorch, Scikit-learn).
- Expertise in AuthAI technologies such as biometrics, continuous authentication, and risk scoring.
- Solid understanding of cybersecurity principles , including intrusion detection, anomaly detection, encryption, and access management.
- Experience with threat intelligence platforms, SIEM tools, and security data analysis .
- Knowledge of cloud platforms (AWS, Azure, or GCP) with security and data services.
- Familiarity with data engineering workflows , including ETL, big data (Spark, Hadoop), and cybersecurity log analysis.
- Strong problem-solving ability with a focus on risk mitigation and predictive analytics .
- Excellent communication skills for collaboration with both technical and non-technical stakeholders.