Data Scientist

About Fuku

About Hytech

Hytech is a leading management consulting firm headquartered in Australia and

Singapore, specializing in digital transformation for fintech and financial services companies. We provide comprehensive consulting solutions, as well as middle- and back-office support, to empower our clients with streamlined operations and cutting edge strategies. Our key clients include top trading platforms and cryptocurrency exchanges.

With a global team of over 2,000 professionals, Hytech has established a strong presence worldwide, with offices in Australia, Singapore, Malaysia, Taiwan, Philippines, Thailand, Morocco, Cyprus, and more.

Drive the ML/DL research agenda for our client-classification engine and adjacent transaction risk control/anti-fraud scenarios across the trading chain. Take the best ideas to production—safely, fast, and cost-effectively. You’ll own the end-to-end experiment loop, from hypothesis → backtest → calibration → monitored rollout, so our routing and control decisions improve broker P&L, stability, and abuse prevention.

Responsibilities

• Be the key owner for modeling research execution: turn business and user questions into measurable data solutions; collaborate with analysts and engineers to build, test, and iterate.
• Explore and apply ML/DL models: experiment with a variety of algorithms to solve practical integrity and classification problems.
• Tackle related challenges: work on areas like user behavior modeling, fraud/anomaly detection, reputation/risk scoring, or abuse prevention, depending on business needs.
• Own the experiment loop: design fair, time-aware evaluation strategies;
• conduct robust backtesting and validation; clearly report findings and next steps.
• Partner for production: collaborate with engineers to ship models safely, monitor health, and set up retraining or recalibration triggers.
• Communicate clearly: write concise design docs and experiment summaries that both technical and business stakeholders can act on.
• Experimentation at scale: hands-on with tuning, validation, and reproducibility on large datasets or distributed compute (e.g., Spark/Databricks, MLflow).

Requirements

• Working with imperfect data: familiar with handling noisy, incomplete, or partially labeled data (e.g., semi-supervised or weak supervision).
• 5+ years in Data Science/ML/DL, with a track record of using data and models to solve practical business or user problems.
• Strong Python and SQL; able to write clean, reproducible analysis code in notebooks or scripts.
• Hands-on with at least one ML or DL library (scikit-learn, PyTorch, TensorFlow).
• Solid experiment design fundamentals: careful validation, fair metrics, and an eye for avoiding data pitfalls.
• Effective communicator: able to summarize findings and decisions for both technical and non-technical partners.

Preferred

Advanced (Plus)

• Deep learning and time-series: comfortable exploring neural network models (e.g., LSTM, GRU, Transformers) or advanced architectures for temporal/user sequence data.
• Representation learning: experience with embeddings, autoencoders, or other feature-learning approaches to improve prediction or personalization.
• Business/context awareness: able to connect modeling choices to real-world metrics and user/business value.
• Experience in integrity, fraud, abuse, personalization, recommendations, search, ads, or growth analytics.
• Familiarity with cloud analytics stacks (Spark/Databricks/MLflow) or large-scale experimentation.
• Exposure to classification, anomaly detection, or user segmentation in any domain.

Data Scientist

Fuku · Singapore, Singapore · Full-time · Posted 2026-11-12

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[Apply at Fuku](https://apply.workable.com/fuku/j/857D6E1CF5/apply)