Data Analyst

 About Flipster

) is a high-performance crypto perpetuals trading platform on a mission to create the most efficient, frictionless, and high-performance trading experience.

Engineered by traders and optimized for trading, Flipster combines zero spreads, instant execution, and capital efficiency to deliver a platform where performance is the product.

Operating globally and serving users in nearly 200 countries, Flipster is built for crypto traders who demand the ultimate perpetual trading experience — from active retail users to degens to seasoned pros — while maintaining the highest standards of compliance and security.

• Collaborate closely with product managers and designers to ensure data-driven product development and feature optimization.
• Conduct objective and statistical analyses, providing actionable insights that drive better decisions.
• Measure various performance outcomes, infer causal relationships, identify key issues, and propose data-driven solutions.
• Design and implement A/B testing experiments to evaluate and optimize product features and user engagement.
• Provide comprehensive data support across the company, including building dashboards, and message bots to enhance data accessibility.

• Bachelor's degree in Data Science, Statistics, Computer Science, Finance, or a related field
• A minimum of 3 years of experience in analytics or a similar role.
• Proficient in SQL and comfortable working with large datasets.
• Experience in conducting product analysis from multiple angles (e.g., cohort analysis, retention, LTV, AARRR framework).
• Experience in designing and implementing the hypothesis and tests (e.g., A/B test) that led to product improvements.
• Business-level proficiency in Korean or English. 

• Familiarity with BigQuery, Python, Airflow, Looker or similar technologies.
• Previous experience working in a cryptocurrency exchange or fin-tech company.
• Exposure to performance marketing strategies and data analysis.
• Interest or skills in data quality checks and debugging for data integrity, as well as query optimization.
• Experience in machine learning, deep learning and/or AI applications.
• Self-driven, proactive personality with strong critical thinking skills.
• Excellent communication skills, with the ability to convey complex ideas clearly and effectively.
• Strong problem-solving skills, with a quick learning ability and adaptability in fast-paced environments.

• Resume/CV submission
• 1st round interview 
• 2nd round interview
• 3rd round interview