Junior Data Analyst

About RedotPay

RedotPay is a global crypto payment fintech integrating blockchain solutions into traditional banking and finance infrastructure. Our user-friendly crypto platform empowers millions globally to spend and send crypto assets, ensuring faster, more accessible, and inclusive financial services. RedotPay advances financial inclusion for the unbanked and supports crypto enthusiasts, driving the global adoption of secure and flexible crypto-powered financial solutions. Join us in shaping the future of finance and making a meaningful impact on a global scale.

Position Overview

We are seeking a Senior Data Analyst with deep industry experience. In this role, you will dive into massive user behavior and transaction data, be responsible for establishing core business metric systems, and provide critical data-driven decision support for risk control strategies, user growth, and product optimization.

Key Responsibilities

• Metric System Development: Build and iterate on metric systems for core fintech businesses (e.g., lending, wealth management, payments, etc.). Design automated monitoring dashboards to promptly detect business anomalies and identify root causes.
• Growth & Refined Operations: Conduct modeling and analysis of user lifetime value (LTV). Deeply explore acquisition channels, retention rates, conversion funnels, and customer acquisition cost (CAC) to provide high-ROI allocation recommendations for marketing spend and operational strategies.
• Product & Campaign Evaluation: Design and execute A/B testing frameworks to scientifically assess the impact of new product features or marketing campaigns.
• Data Infrastructure Development: Collaborate closely with data engineering teams to advance the modeling and consolidation of core business data warehouses.
• Team Enablement: Codify analytical methodologies and mentor junior and mid-level data analysts to elevate the team's overall data expertise.

Qualifications

• Bachelor's degree or above in Mathematics, Statistics, Computer Science, Financial Engineering, Economics, or related fields.
• 1 year of experience in data analytics
• Proficient in SQL, with the ability to handle large-scale, complex datasets and strong query optimization skills.
• Knowledgeable in Python or R, capable of independently performing data cleansing and statistical modeling (e.g., logistic regression, cluster analysis, time series, etc.).
• Proficient in mainstream BI tools (e.g., Tableau, Power BI, QuickBI, etc.) for data visualization.
• Solid foundation in statistics, with a deep understanding of hypothesis testing, A/B testing principles, and traffic funnel models.