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Skills:

Statistics, Python, SQL

Job type:

Full-time

• Lead the end-to-end development of analytics and AI projects that strengthen business and customer intelligence across the Siam Piwat data ecosystem.
• Translate business challenges into data science solutions that deliver measurable outcomes and strategic value.
• Collaborate with MIS, Data Engineering, Data Analytics and Business teams to ensure reliable data flow, technical integration, and sustainable implementation.
• Drive analytics initiatives that inform sales strategies, tenant insights, and evolving market opportunities.
• Technical Execution & Supervision.
• Develop and deploy predictive models and analytics frameworks to understand performance patterns, identify growth drivers, and support decision-making.
• Provide technical direction and support to data scientists and analysts to maintain consistency, accuracy, and quality of analytical outputs.
• Apply best practices in data preparation, model governance, and MLOps to ensure scalability and reliability.
• Work closely with cross-functional partners internally and externally to transform analytical insights into actionable business recommendations.
• Business Impact & Innovation.
• Deliver insights that enhance understanding of customer behavior, tenant performance, and overall sales and customer trends.
• Monitor and assess emerging market and consumer trends to guide future business strategies.
• Present complex findings through clear visualizations and storytelling tailored for executive and business audiences.
• Foster a culture of innovation and continuous improvement in analytics practice.
• Education & Experience.
• Master s or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative discipline.
• Minimum 5-7 years of experience in data science, advanced analytics, or AI solution delivery..
• Demonstrated success in developing and implementing data-driven solutions with measurable business impact.
• Experience in retail, customer analytics, or digital transformation environments is preferred..
• Technical Skills.
• Proficiency in Python, SQL, and PySpark for data analysis and model development..
• Solid understanding of machine learning, AI, and statistical modeling frameworks..
• Familiarity with cloud data platforms (DWS, AWS, GCP, or Azure) and version control tools (Git)..
• Experience with visualization and BI tools such as Power BI, Tableau, Apache Superset, or similar..