Data Scientist

Hytech; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

Hytech in Singapore is seeking a highly analytical Data Scientist to join the data platform & intelligence team. You will translate complex datasets into actionable business strategies and build ML models that support predictive, automated decision-making.

Responsibilities include deep-dives into customer behavior and performance metrics, designing ML models (forecasting, anomaly detection, segmentation), building real-time pipelines with SQL and Python, and communicating insights to leaders.

Qualifications

• Bachelor's or Master's in a quantitative field.
• Ability to query large databases and optimize SQL performance.
• Strong Python skills for data manipulation (Pandas, NumPy).
• Hands-on ML with frameworks such as scikit-learn, XGBoost, TensorFlow or PyTorch.
• 5+ years in data analysis or data science solving real-world problems.
• Exceptional data storytelling, explaining the why and impact.
• Fluent English and Mandarin communication.
• Fintech experience or financial data context is desirable.

Responsibilities

• Deep-dive into customer behavior, business performance, and metrics to identify growth opportunities and risks.
• Design, build, train, and deploy ML models for predictive insights and automated decisions.
• Identify data abnormalities and perform root-cause analysis for stakeholders.
• Develop automated data pipelines and dashboards using SQL and Python for real-time reporting.
• Translate model outputs into concise executive summaries for leaders.
• Collaborate between data engineering and business units to align solutions with needs.

Skills

SQL querying

Python scripting

Machine learning

Data visualization

Storytelling with data

Cross-functional collaboration

Bilingual communication

Education

Bachelor's or Master's in quantitative field

Tools

SQL

Pandas

NumPy

scikit-learn

XGBoost

TensorFlow

PyTorch

MLflow

Job description

Job Summary

We are looking for a highly analytical and business-savvy Data Scientist to join our data platform & intelligence 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.