Astra Tech is a UAE-based technology investment and development group, embarked on a mission to build the world’s first ultra platform & ecosystem, that will disrupt the consumer technology space by rethinking the boundaries of a digital ecosystem.
It will be the first of its kind in the MEA region to simplify the way people & businesses interact, engage, and transact with each other. The platform will provide seamless connectivity between consumers and businesses, enabling users to effortlessly access home, e-commerce, and fintech services in one place. Astra’s mission is to enrich people’s lives by making communication and e-commerce more seamless, connected, and natural.
Key Responsibilities
We are seeking a highly skilled and motivated Fintech Security Expert to join our team and play a pivotal role in safeguarding our organization's digital assets, financial transactions, and business operations. The ideal candidate will possess a deep understanding of the security challenges faced by the fintech industry, practical expertise in real-time risk assessment, multi-dimensional risk identification, and a demonstrated ability to integrate advanced risk management tools and methodologies. This role is integral to ensuring compliance with industry standards and regulations, reducing fraud and financial losses, maintaining customer trust, and supporting business innovation in areas such as credit, insurance, and investment security.
Security Architecture & Compliance:
- Design, implement, and maintain a comprehensive payment security architecture aligned with fintech industry best practices and regulatory requirements (e.g., PCI DSS, PCI PIN, PCI 3DS, UAE-IAR NESA).
- Ensure continuous compliance with financial industry security standards and frameworks, as well as anti-money laundering (AML) and anti-fraud mandates.
Real-Time Risk Assessment & Monitoring:
- Develop and implement systems for real-time risk assessment of user behavior, transactions, and device fingerprints, proactively identifying and blocking fraudulent activities.
- Leverage multi-dimensional risk identification techniques—such as analyzing IP addresses, historical records, and behavioral patterns—to detect emerging threats like account theft, fake identities, and anomalous transactions.
Risk Rule Engine & Automated Risk Management:
- Utilize risk engines to rapidly configure, update, and optimize prevention rules that address specific fraud scenarios (e.g., false refunds, order-padding).Implement automated risk management protocols to dynamically respond to high-risk events, such as blocking transactions, limiting account functionalities, or triggering secondary verifications without manual intervention.
- Continuously improve and refine these models through model training and real-time optimization, adapting to new threat vectors and enhancing predictive accuracy.
Abnormal Behavior Detection & Monitoring:
- Detect and investigate abnormal behavior patterns, such as atypical spending, repeated failed attempts, high-frequency transactions, and suspicious fund flows, helping prevent money laundering and other illicit activities.
- Establish risk monitoring and early warning systems with visual dashboards and alerts, enabling swift detection and response to risks.
Main Application Scenarios & Business Alignment:
- Apply advanced security measures to payment security, anti-fraud, credit risk control, insurance anti-fraud, money laundering monitoring, marketing risk management, and investment security.
- Align security initiatives with core business goals, such as preventing fund losses, enhancing customer trust, complying with regulations, reducing operational costs, and supporting the growth of innovative products and services.
Qualifications
- Bachelor's degree in computer science, Information Security, or a related field.
- Proven experience in fintech security with a solid grasp of industry-specific threats, fraud typologies, and protective measures.
- Ability to understand complex business needs and translate them into effective, scalable security strategies that support real-time risk assessment, multi-dimensional analysis, and automated risk management. Deep knowledge of financial and payment frameworks, standards, and best practices, including familiarity with AML and credit risk modeling methodologies.
- Strong technical skills, including proficiency in security tools, rule engines, device fingerprinting technologies, cryptographic solutions, and machine learning-based risk scoring systems.
- Excellent analytical and problem-solving abilities with a track record of detecting, mitigating, and preventing various forms of digital fraud.
- Strong communication and interpersonal skills, capable of explaining technical risks and mitigations to diverse stakeholders.
- Industry certifications in cybersecurity (e.g., OSCP, OSDE, CREST) are preferred.
