Job Summary We are seeking an analytical, data-driven, and highly technical Data Scientist to join our advanced analytics and operations team. In this critical role, you will be the core technical owner responsible for designing, building, and optimizing end-to-end predictive pipelines, statistical algorithms, and data modeling architectures. Operating at the intersection of data engineering, software product development, and front-office business desks, you will translate multi-layered transactional and behavioral data into actionable insights that maximize conversion and corporate efficiency. The ideal candidate will combine strong systematic backend logic with advanced statistical analysis to build high-performance data tracks while maintaining absolute data integrity.
Key Responsibilities
- Predictive Model Architecture: Design, train, evaluate, and deploy scalable machine learning architectures, statistical algorithms, and deep data-routing rules to tackle complex operational challenges.
- Data Pipeline Optimization: Extract, transform, and clean high-volume structured and unstructured datasets across multi-cloud infrastructure and centralized data lakes.
- A/B Testing & Experimentation: Formulate and execute rigorous A/B testing plans, statistical modeling paradigms, and hypothesis testing matrices to optimize software performance and feature adoption.
- Feature Engineering & Analytics: Build and maintain dynamic database querying pipelines, create predictive features, and develop deep customer segmentation matrices using advanced logical logic.
- Performance Dashboards & Briefings: Interpret model execution logs and compile comprehensive data visualization charts, real-time analytics reports, and strategic briefs for management review.
- System Troubleshooting & Maintenance: Monitor system outputs for latency risks, prediction drops, or integration errors, debugging deployment scripts promptly to preserve code uptime.
- Data Governance & Compliance: Enforce strict data security standards across all modeling datasets, ensuring all target tracking and pipeline routing strictly comply with corporate policy and the Personal Data Protection Act (PDPA).
Requirements
- Education: Minimum Bachelor’s Degree (Master's or Ph.D. preferred) in Computer Science, Data Science, Statistics, Mathematics, Business Analytics, or a highly quantitative STEM field.
- Technical Stack: Deep engineering knowledge of core programming languages (Python or R), structural machine learning packages (scikit-learn, TensorFlow, or PyTorch), and advanced relational database querying using SQL.
- Tools & Cloud Systems: Proven experience navigating cloud data platforms (AWS, Microsoft Azure, or GCP), big data frameworks (Spark or Hadoop), and deploying containerized code frameworks (Docker).
- Experience: Prior hands-on experience (2–5 years) as a Data Scientist, Machine Learning Engineer, or Advanced Data Analyst—preferably within an enterprise SaaS, tech consultancy, fintech, or digital platform provider—is required.
- Core Competencies: Exceptional structural logic, sharp analytical diagnostic skills under tight deployment sprints, intense attention to detail, and a collaborative team-player mindset.
Pay: $3,800.00 - $5,600.00 per month
Work Location: In person