Data Analyst (Mid-Level)

This is a hybrid role based in our Bangkok office, with a remote arrangement for candidates based in Vietnam.

We are seeking an experienced and self-driven Data Analyst (Mid-Level) to join our growing team. This role is ideal for candidates with at least 2 to 4 years of relevant experience who are ready to take ownership of their work and operate with a high degree of autonomy.

As a Data Analyst (Mid-Level), you will go beyond routine reporting - proactively uncovering trends, delivering actionable insights, and helping leading brands across Southeast Asia make smarter decisions in one of the fastest-growing sectors in the region.

Responsibilities:

• Transform, and clean a large complex dataset using Python and SQL
• Develop and implement advanced analytical models and algorithms to uncover trends, patterns, and opportunities in e-commerce data
• Collaborate with cross-functional teams to understand client objectives, define analytical requirements, and deliver customized solutions
• Communicate findings and recommendations effectively through clear visualizations, statistical results, and reports
• Continuously enhance analytical methodologies and processes to improve efficiency and effectiveness
• Stay updated with industry trends and best practices in data analysis and e-commerce

Requirements

• Exceptional analytical and problem-solving skills with a solid foundation in statistics and the ability to independently draw conclusions from complex datasets
• Proficiency in Python, SQL, Google Sheets, and Excel is essential; experience with data visualization tools (e.g., Tableau, Power BI) is a plus
• Proficiency in data warehouse platforms (e.g., Snowflake, Amazon Athena, Google BigQuery) for complex querying, analytics, and pipeline scheduling is essential
• Proactive, curious, and highly tenacious, with a strong drive to grow and stay ahead of industry trends
• Comfortable navigating a fast-paced, ambiguous environment with a high degree of independence
• Passionate about e-commerce, with strong communication skills and the ability to convey technical concepts clearly to non-technical stakeholders; experience with client-facing communication is a plus
• A Bachelor's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Economics, etc.) is preferred but not required.