━━━━━━━━━━━━━━━━━━━━━━━━━━━━ PART 1: JOB DESCRIPTION ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Data Analyst at TechStartup Co. Bangkok, Thailand | Hybrid (3 days on-site) | Full-time ABOUT THE ROLE We are looking for a Data Analyst to transform our growing volume of user data into decisions that drive the product roadmap. You will partner directly with Product and Marketing to surface insights on user behavior, retention, and revenue — and you will own the dashboards our leadership team relies on every week. WHAT YOU WILL DO • Own end-to-end analysis of user behavior, retention, and revenue metrics across all product lines • Build and maintain executive dashboards in Looker Studio for leadership and cross-functional teams • Partner with Product and Marketing to define, run, and interpret product experiments • Translate complex findings into clear, actionable recommendations for non-technical audiences • Proactively surface trends and anomalies before leadership needs to ask • Maintain data quality and contribute to pipeline documentation and analytics best practices WHAT WE ARE LOOKING FOR Must-have: • 2+ years of experience in a data analytics or business intelligence role • Proficient in SQL — you write complex queries daily without hesitation • Hands-on experience with Python or R for data manipulation and statistical analysis • Demonstrated ability to communicate data insights clearly to non-technical stakeholders Nice-to-have: • Experience designing and analyzing A/B tests and product experiments • Familiarity with Google Analytics 4 and marketing attribution modeling • Experience with Tableau or additional BI tools beyond Looker Studio WHAT WE OFFER • Salary: $60,000–$80,000 per year depending on experience • Hybrid schedule: 3 days in Bangkok office, 2 days remote • Comprehensive health insurance for employee and dependents • 20 days annual leave plus all Thai public holidays • Direct access to senior leadership with meaningful ownership from day one HOW TO APPLY Send your CV and a short note about a data project you are proud of to careers@techstartupco.com. We review applications on a rolling basis and aim to respond within five business days. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ PART 2: INTERVIEW QUESTION BANK ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION A — BEHAVIORAL 1. Tell me about a time your analysis directly changed a significant business decision. What to listen for — A clear narrative connecting data work to a real outcome; demonstrated ability to influence stakeholders without direct authority. 2. Describe a situation where you discovered a critical data quality issue. What did you do? What to listen for — Proactive ownership of the problem; a systematic approach to investigating root cause rather than working around it. 3. Tell me about a time you had to explain a complex dataset to a non-technical audience. What was your approach? What to listen for — Use of visuals or storytelling to simplify; genuine empathy for the audience's level of familiarity with data. 4. Describe a situation where you had to make analytical decisions with incomplete or ambiguous data. What to listen for — Comfort with uncertainty; transparency about assumptions made; practical judgment under pressure. 5. Tell me about a time you proactively surfaced an insight that nobody on your team was looking for. What to listen for — Intellectual curiosity and ownership mentality; focus on business impact rather than purely technical exploration. SECTION B — TECHNICAL AND SKILLS 6. Walk me through how you would investigate a sudden 20% drop in daily active users that appeared overnight. What to listen for — Structured hypothesis-driven thinking; familiarity with cohort analysis, funnel breakdown, and segment-level investigation. 7. Describe or write a SQL query to find customers who purchased in the past 30 days but have not returned in the last 7 days, ordered by lifetime revenue. What to listen for — Correct use of filtering and ordering logic; clear reasoning about edge cases and data assumptions. 8. How would you design an A/B test to evaluate whether a new onboarding flow improves 14-day user retention? What to listen for — Statistical rigor including sample size and statistical power; success metrics defined before the test begins. 9. How do you ensure the reliability and accuracy of a dashboard that leadership uses for weekly business decisions? What to listen for — Data validation practices and monitoring; documentation habits; understanding of upstream pipeline risks. 10. What is the difference between correlation and causation? Give a business example where confusing the two led to a poor decision. What to listen for — Conceptual clarity; a grounded and realistic example; critical thinking about how to establish causality. SECTION C — CULTURE FIT AND MOTIVATION 11. What does a healthy data culture look like to you, and how have you helped build one in a past role? What to listen for — Advocacy for data literacy across teams; a realistic view of organizational data maturity. 12. How do you prioritize your work when multiple stakeholders request analysis at the same time? What to listen for — A structured prioritization framework tied to business impact; clear and respectful communication when declining or deferring requests. 13. What types of analytical problems genuinely excite you? What to listen for — Authentic enthusiasm for problem types relevant to this role; alignment with the company's core challenges. 14. How do you stay current with tools, methods, and developments in the data analytics field? What to listen for — Self-directed learning habits; specific resources or communities; intellectual curiosity beyond what the job requires. 15. Where do you hope to be professionally in three years, and how does this role fit that path? What to listen for — Realistic and grounded ambition; alignment between personal goals and what this position genuinely offers. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ PART 3: CANDIDATE EVALUATION SCORECARD ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ | Competency | Weight | Score (1–5) | Notes | |--------------------------|--------|-------------|-------| | SQL and Technical Skills | 30% | | | | Analytical Thinking | 25% | | | | Communication Skills | 20% | | | | Business Acumen | 15% | | | | Culture and Values Fit | 10% | | | | Total | 100% | | |