Job Scope:
- Engage with various stakeholders and cybersecurity teams to deeply understand evolving challenges related to unauthorized privileged access and identify opportunities for data-driven solutions.
- Design, develop, and deploy advanced machine learning models and analytical techniques to detect anomalous behavior and potential security breaches.
- Continuously monitor and evaluate model performance iterate to improve detection accuracy and reduce false positives.
- Collaborate with engineering teams to build scalable and reliable production systems that operationalize detection models.
- Lead, mentor, and support the engineering team, fostering their technical growth and development.
- Communicate complex findings and insights clearly to both technical and non-technical stakeholders, driving data-informed decision-making.
- Lead project planning and timeline management to ensure timely delivery of analytics solutions.
Job Requirements:
- Proven experience (typically 5+ years) in data science or machine learning roles, preferably within cybersecurity or fraud detection domains.
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field. PhD preferred.
- Strong expertise in anomaly detection, behavioral analytics, and classification models.
- Hands-on experience with Python, R, or similar programming languages and relevant ML libraries (e.g., scikit-learn, TensorFlow, PyTorch).
- Familiarity with cybersecurity concepts, especially around privileged access management, threat detection, and risk mitigation.
- Experience working with large-scale datasets, data pipelines, and cloud environments.
Working hours:
Mondays to Fridays: Office hours
Contract Period: 1/9/2025 to 31/8/2027
Location: Mapletree Business City
EA License No.: 96C4864
Reg No.: R25128798 HUANG QIMENG
