Data Scientist

About Us
- Hytech is a leading management consulting firm headquartered in Australia and Singapore.
- The company specializes in digital transformation for fintech and financial services companies.
- Hytech provides comprehensive consulting solutions, as well as middle- and back-office support, to empower clients with streamlined operations and cutting-edge strategies.
- 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.
Job Summary
We are seeking a highly analytical and business-savvy Data Scientist to join our data platform & intelligence team. The ideal candidate will be adept at translating complex datasets into clear, actionable business strategies and building machine learning models that enable predictive, automated decision-making. Responsibilities include detecting business abnormalities, conducting deep-dive root cause analysis, developing predictive and analytical models, and delivering high-level summaries to guide internal leaders and global clients.
Key Responsibilities
- Conduct deep-dive analysis into customer behavior, business performance, and operational metrics to identify growth opportunities and potential risks.
- Design, build, train, and deploy machine learning models (such as forecasting, classification, anomaly detection, customer segmentation, and churn/risk prediction) to drive predictive insights and automate decision-making at scale.
- Proactively identify data abnormalities (e.g., performance dips, operational shifts) and perform comprehensive root cause analysis to provide clarity to stakeholders.
- 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.
- Translate complex technical findings and model outputs into concise executive summaries and natural language insights for non-technical business leaders.
- 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
- Bachelor’s or Master’s degree in a quantitative field (e.g., Computer Science, Statistics, Data Science, Machine Learning, or Finance).
- Proven ability to query large, complex databases and optimize performance using SQL.
- Strong coding skills in Python for data manipulation (Pandas, NumPy) and automated analysis.
- Hands-on experience building and deploying machine learning 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.
- Minimum of 5 years’ experience in data analysis or data science, specifically in identifying business trends and solving real-world problems.
- Exceptional ability to synthesize data and "tell a story," explaining not just the "what" but also the "why" and "so what" in clear business terms.
- Strong communication skills, with fluency in English and Mandarin, to effectively collaborate with diverse, cross-functional teams.
- Experience in Fintech (Crypto, Trading, Banking) or related financial data environments is highly desirable.