Data Scientist

About Us

Hytech is a global management consulting firm headquartered in Australia and Singapore, specializing in digital transformation for fintech and financial services companies. We empower our clients with comprehensive consulting solutions and robust middle- and back-office support, enabling streamlined operations and forward-thinking strategies.

With a team of over 2,000 professionals, Hytech serves a diverse portfolio of clients, including the world's second-largest CFD trading platform and several leading cryptocurrency exchanges. Our global presence spans across Australia, Singapore, Malaysia, Taiwan, the Philippines, Thailand, Morocco, Cyprus, and more.

Job Summary

We are looking for a highly analytical and business-savvy Data Scientist to join our global business intelligence & strategy team. The ideal candidate is a data master who can translate complex datasets into clear, actionable business strategies, and build machine learning models that turn data into predictive, automated decision-making. You will be responsible for detecting business abnormalities, performing deep-dive root cause analysis, developing predictive and analytical models, and delivering high-level summaries that guide our internal leaders and global clients.

Key Responsibilities

• Business Intelligence & Analysis: Deep-dive into customer behavior, business performance, and operational metrics to identify growth opportunities and potential risks.
• Machine Learning & Modeling: Design, build, train, and deploy machine learning models (e.g., forecasting, classification, anomaly detection, customer segmentation, churn/risk prediction) to drive predictive insights and automate decision-making at scale.
• Root Cause Investigation: Proactively identify data abnormalities (e.g., performance dips, operational shifts) and perform comprehensive root cause analysis to provide clarity to stakeholders.
• Technical Execution: Develop and optimize automated data pipelines and dashboards using SQL and Python to ensure high-quality, real-time reporting, and operationalize models into production-ready workflows.
• Synthesis & Communication: Translate complex technical findings and model outputs into concise executive summaries and natural language insights for non-technical business leaders.
• Strategic Collaboration: Act as a bridge between data engineering and business units to ensure analytical and modeling solutions are perfectly aligned with real-world business needs.

Qualifications

• Educational Background: Bachelor's or Master's degree in a quantitative field (e.g., Computer Science, Statistics, Data Science, Machine Learning, or Finance).
• Technical Mastery: Proven ability to query large, complex databases and optimize performance using SQL.
• Proficient Python: Strong coding skills for data manipulation (Pandas, NumPy) and automated analysis.
• Machine Learning Expertise: Hands-on experience building and deploying ML models using frameworks such as scikit-learn, XGBoost, TensorFlow, or PyTorch, including feature engineering, model evaluation, and tuning. Familiarity with MLOps practices (model deployment, monitoring, and versioning) is a plus.
• Business Analysis Experience: 5+ years of experience in data analysis or data science, specifically in identifying business trends and solving real-world problems.
• Synthesizing Ability: Exceptional ability to tell a story with data, moving beyond the what to explain the why and so what in clear business terms.
• Communication: Strong communication skills, with fluency in English and Mandarin, to effectively collaborate with diverse, cross-functional teams.
• Industry Context: Experience in Fintech (Crypto, Trading, Banking) or related financial data environments is highly desirable.