About Hytech
Hytech is a leading management consulting firm headquartered in Australia and Singapore, specialising in digital transformation for fintech and financial services organisations.
We deliver end-to-end consulting services and robust middle- and back-office solutions that enable our clients to optimise operations, enhance efficiency, and stay ahead in a fast-evolving digital landscape. Our client portfolio includes top global trading platforms and leading crypto exchanges.
We apply AI and data-driven approaches to real-world financial use cases, including risk management, process optimisation, and decision support, with a focus on delivering practical impact. With more than 2,000 professionals worldwide, Hytech has a strong and growing international presence, with offices across Australia, Singapore, Malaysia, Taiwan, the Philippines, Thailand, Morocco, Cyprus, Dubai, and beyond.
About the Role
We are looking for a Detection Lead to own and advance our real-time detection capabilities across a high-volume trading environment.
This is a senior, hands-on role for someone who understands how to identify unusual behaviours, emerging patterns, system anomalies, and financial irregularities from complex, high-noise data.
You will lead the development and continuous improvement of detection logic and capabilities, working at the intersection of trading, risk, data engineering, and AI/ML. You will also drive the day-to-day priorities and execution of the Detection Squad, turning complex signals into scalable, production-ready detection solutions.
What You Will Do
- Own the end-to-end detection framework across trading activity, client behaviour, system anomalies, and financial irregularities.
- Define and continuously optimise detection logic, signal scoring frameworks, and dynamic thresholds.
- Lead the daily priorities and execution of the Detection Squad, ensuring detection initiatives move effectively from concept through to production.
- Analyse large-scale, high-noise, multi-source data, including trading logs, user activity, system metrics, and financial outcomes, to identify actionable signals.
- Design and optimise real-time detection pipelines with low-latency requirements for critical events.
- Develop and continuously improve anomaly detection, behavioural clustering, and pattern recognition capabilities using both rule-based and ML approaches.
- Build continuous feedback loops from incident identification and root-cause analysis through to model refinement and retraining.
- Translate complex detection requirements into clear technical specifications and work closely with engineering teams on implementation.
- Partner with trading, risk operations, data engineering, and infrastructure teams to strengthen detection coverage and system alignment.
- Continuously reduce false positives while maintaining strong detection precision and coverage.
What We Are Looking For
- 5–10 years of experience in real-time detection, trade surveillance, fraud/risk analytics, AI/ML within financial services, trading, crypto exchanges, fintech, or large-scale internet platforms.
- Hands-on experience building and owning detection or anomaly detection systems end to end.
- Strong applied knowledge of anomaly detection, behavioural analytics, pattern recognition, and real-time model deployment.
- Experience working with streaming or event-driven data technologies such as Kafka, Flink, KDB/q, or equivalent.
- Strong systems thinking, with the ability to connect signals across multiple domains and translate ambiguous problems into structured detection logic.
- Exposure to market manipulation detection, trade surveillance, or exchange-level risk monitoring would be an advantage.
- Experience with graph-based detection, knowledge graphs, fraud network analysis, or behavioural clustering is desirable.
- Fluency in both English and Mandarin Chinese for effective cross-regional collaboration.
